Beta Rhythm (Music of the Mind)

Magnetoreception - a gift from Mars

2011-12-22T09:25:00.001-08:00

I've been finding lately that if you look deeply into just about any aspect of life it quickly becomes fascinating. Like migration, for instance...

The story starts with something called 'magnetotactic bacteria' - bacteria that have DNA that creates tiny magnetite (Fe[sub]3[/sub]O[sub]4[/sub]) particles that can act as tiny compasses...

From Magnetotactic bacteria
Magnetites from magnetotactic bacteria MV-1 are elongated. The elongation adds to the magnetic pull of these tiny compasses and thus helps the bacteria locate sources of food and energy. This team of authors found that the elongation was accomplished by the addition of six faces, shown in red in the figure [above]. "The process of evolution on Earth has driven magnetotactic bacteria to make perfect little bar magnets, which differ strikingly from anything found outside biology," says coauthor Joe Kirschvink

And it turns out that birds, sea turtles and salmon also have these tiny magnetite crystals... From The Physics and Neurobiology of Magnetoreception:

Evidence for a magnetic map in sea turtles.
Juvenile sea turtles establish feeding sites in coastal areas and home back to these sites if displaced. To investigate how turtles navigate to specific sites, juvenile green turtles were captured in their coastal feeding areas near Melbourne Beach, Florida. Each turtle was tethered to an electronic tracking system and placed in a pool of water. The pool was surrounded by a magnetic coil system that could be used to replicate the magnetic fields that exist at two distant sites. Turtles exposed to a magnetic field that exists ~330 km north of their feeding grounds oriented southward, whereas those tested in a field that exists an equivalent distance to the south swam north. Therefore, turtles responded to each field by swimming in the direction that would have led towards the feeding area had they actually been in the locations at which the magnetic fields exist.

The results indicate that sea turtles have a type of ˜magnetic map' that facilitates navigation to specific geographical areas.

And scientists are starting to figure out how this 'magnetic sense' works...
From Homing in on Vertebrates
Joseph L. Kirschvink, Nature - 1997
...
All known sensory systems have specialized receptor cells designed to respond to the external stimulus, and these are always coupled to neurons to bring this information to the brain.
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It took nearly two decades to realize that the geomagnetic compass used by adult birds was programmed to be ignored if other orientation cues (such as a Sun or star compass, polarized skylight, infrasound and ultrasound) were present. These orientation cues constitute a complex but consistent web of interacting responses, which are used not only by birds but in all major vertebrate groups and many invertebrates.

What's truly mind blowing is there is compelling evidence that the magnetotactic bacteria that started all of this originated on Mars!
From Magnetite-based magnetoreception
Magnetoreception may well have been among the first sensory systems to evolve, as suggested by the presence of magnetosomes and magnetosome chain structures in the 4.0 billion year old carbonate blebs of the Martian meteorite ALH84001. Although this is nearly half a billion years older than the oldest microbial fossils on Earth, it suggests that this genetic ability was brought here from Mars via the process of panspermia. In terms of the evolutionary arguments presented above, the striking similarity in magnetosome structure and organization in bacteria, protists, and vertebrates, and the deep fossil record, supports the hypothesis that magnetite biomineralization system arose initially in the magnetotactic bacteria and was incorporated into eukaryotic cells through endosymbiosis; later, it may even have been used as a template to drive the widespread biomineralization events during the Cambrian explosion.

Diffusion Imaging - Mapping the Connectome

2011-12-14T10:31:00.000-08:00

From The Human Connectome Project Is a First-of-its-Kind Map of the Brain's Circuitry:
Working with $30 million and just half a decade, the Human Connectome Project aims to create a first-of-its-kind map of the brain’s complex circuitry, detailing every connection linking thousands of different regions of the brain. ...
The project aims to tap state-of-the-art brain scanning technologies, including diffusion imaging, various MRI methods, and magnetoencephalography to map not just how messages move through the brain, but how various regions work together via networks and networks of networks to achieve the complexity that is the human mind. With map resolutions down to the voxel – small swaths of grey matter containing about one million neurons each – researchers estimate the HCP will generate about one petabyte of data, which will require its own supercomputer to process.

All that scanning, data gathering, and analysis should pay off though, HCP researchers say. The end result will be an open platform that other neuroscientists can use to test their own theories, hypotheses, and findings against. Such a map should help scientists find their way to deeper understandings of how the brain works as well as cures for complicated neurological disorders.

Diffusion Tensor Magnetic Resonance Imaging:

Understanding Diffusion MR Imaging Techniques: From Scalar Diffusion-weighted Imaging to Diffusion Tensor Imaging and Beyond by Patric Hagmann et. al provides a nice overview of how Diffusion Tensor MRI works. Basically, MRI is used to detect the displacement distribution (a.k.a. diffusion) of water molecules along the 'pipes' formed by axons in the brain. Experimental evidence suggests that the tissue component predominantly responsible for the anisotropy of molecular diffusion observed in white matter is not myelin, as one might expect, but rather the cell membrane. The degree of myelination of the individual axons and the density of cellular packing seem merely to modulate anisotropy. Furthermore, axonal transport, microtubules, and neurofilaments appear to play only a minor role in anisotropy measured at MR imaging. In a conventional MRI, every 3D position is assigned a grey-level value, whereas Diffusion Tensor MRI assigns it a 3D image that encodes the molecular displacement distribution.

Hubs and Networks
Some interesting findings are already starting to be discovered using this technology. From Study: A rich club in the human brain:

"We've known for a while that the brain has some regions that are 'rich' in the sense of being highly connected to many other parts of the brain," said Olaf Sporns, professor in the Department of Psychological and Brain Sciences in IU's College of Arts and Sciences. "It now turns out that these regions are not only individually rich, they are forming a 'rich club.' They are strongly linked to each other, exchanging information and collaborating."

The study, "Rich-Club Organization of the Human Connectome," is published in the Nov. 2 issue of the Journal of Neuroscience. The research is part of an ongoing intensive effort to map the intricate networks of the human brain, casting the brain as an integrated dynamic system rather than a set of individual regions.

Using diffusion imaging, which is a form of MRI, Martijn van den Heuvel, a professor at the Rudolf Magnus Institute of Neuroscience at University Medical Center Utrecht, and Sporns examined the brains of 21 healthy men and women and mapped their large-scale network connectivity. They found a group of 12 strongly interconnected bihemispheric hub regions, comprising the precuneus, superior frontal and superior parietal cortex, as well as the subcortical hippocampus, putamen and thalamus. Together, these regions form the brain's "rich club."

Most of these areas are engaged in a wide range of complex behavioral and cognitive tasks, rather than more specialized processing such as vision and motor control. If the brain network involving the rich club is disrupted or damaged, said Sporns, the negative impact would likely be disproportionate because of its central position in the network and the number of connections it contains. By contrast, damage to regions outside of the rich club would likely cause specific impairments but would likely have little influence on the global flow of information throughout the brain.

Sporns said the cohesive nature of the rich club's interconnections was surprising and unexpected. It would not have been implausible to have highly connected nodes that did not interact or influence each other to the same degree.
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"It's a group of highly influential regions that keep each other informed and likely collaborate on issues that concern whole brain functioning," he said.

Connectivity vs. Functionality
One of the things I find both annoying and almost funny is the marketing language that is being used for supercomputing simulations that try to equate the number of computations per second a supercomputer can make to an 'equivalent' level of neurobiology. IBM says that they can apparently do 'cat-scale' simulations. This, in spite of the fact that we don't fully understand how even the simplest neural networks work at a detailed level. Neurobiologist Henry Markram has gone as far as calling the IBM Cat Scale Brain Simulation a Hoax.

So it's important to take a step back and look at how this work fits into the larger scheme of things... From a comment made by Olaf Sporn in Brian Science Podcast interview with Olaf Sporn:
I think it would be simple-minded to reduce the brain to a wiring diagram. That’s certainly not my intention, and I think it would be simple-minded if one were to propose that. You mentioned the worm, C. elegans, earlier. It has about 300 neurons—something like that—fairly stereotypically connected to each other. And we’ve known that particular wiring diagram now for 25 years, as a result of the heroic efforts of researchers who reconstructed this meticulously in the early ‘80s. But we still don’t really understand how the nervous system of C. elegans works in its entirety.

So, it is something that we need to know—sort of like the genome. We really do want that information. But it doesn’t fully explain the functioning of the organism or of the nervous system; it only gives us a foundation. It’s necessary, but not sufficient.

Concussions
In addition to mapping connectivity in the brain, Diffusion Tensor Imaging (DTI) is also providing insight into brain injuries such as concussions. From Dr. Randall Benson (quoted in the Brain Damage Blog (Jan 8, 2010): ):

Closed head injuries (non-penetrating) including concussion are caused by sudden acceleration or deceleration of the head which causes local deformations of the brain within the cranium. The anatomical and biomechanical properties of the brain are such that white matter fibers are stretched and damaged, resulting in diffuse axonal injury (DAI) which is the hallmark pathology and accounts for most of the neurological disability in TBI (Traumatic Brain Injury).

The typical cognitive deficits in TBI, i.e., slowed information processing, decreased attention and memory, and psychiatric symptoms are caused by damage to the “cables” which allow for efficient transmission of information between neurons. TBI reduces brain network efficiency resulting in decreased capacity and global functional impairment. Concussive injury such as occurs in football with high speed collisions also causes deformation of brain substance and is felt to account for many of the immediate and delayed symptoms including the post-concussive syndrome. ERP studies of sports related concussion suggest that symptomatic recovery may occur while neurologic and brain metabolic functioning continues to be impaired from weeks to months after injury.

Incurring a second concussion before neurologic recovery has been shown to worsen outcome and may begin a downward spiral culminating in chronic traumatic encephalopathy (CTE) but this is not known. Diffusion tensor imaging (DTI) is able to detect damaged white matter fibers (axons) which have altered flow of water molecules compared with healthy axons.

More:

	Check out the Brian Science Podcast interview with Olaf Sporn, which covers the work he has been doing on brain networks.
	Networks of the Brain by Olaf Sporns.

Junk DNA: "Listen to your junk man - he's singing"

2009-06-17T20:12:00.000-07:00

"Listen to your junk man - he's singing ... All dressed up in satin, walking past the alley..." - Bruce Springsteen, New York Serenade

Junk DNA is looking mighty fine lately. Only a few years ago, the non-coding regions of DNA that make up over 95% of the genome were looked upon as the uninteresting desert wastelands between the regions of DNA involved in protein synthesis. How times have changed!

'Junk' DNA not junk but key to complexity

There's a very nice video on Gene Regulation(free) from Science Magazine that discusses the pivotal roles that these non-coding regions of DNA play in our genome.

As John Mattick of The University of Queensland states at the end of the video:"We're just realizing that we've only got to first base and we have a long way to go, and most of the journey forward is going to be dissecting, analyzing and rebuilding an understanding of the massively parallel and extremely sophisticated RNA regulatory circuits, which really do underpin our complexity. And the irony, I think, is that what was dismissed as junk, because it wasn't understood, will turn out to hold the secret of human complexity, including our cognitive complexity. And that's where were going over the next 10 to 15 years.

More info on John Mattick's work is provided by a News in Science article (May 10,2004):The researchers scanned the human, rat and mouse genomes for matching regions of 200 or more DNA base pairs and found 481 regions that were completely unchanged. They then looked at earlier organisms.

"We then looked at the dog and bovine genomes and found that they were preserved there. Amazingly, most of them were preserved in the chicken genome, which has just been released, and about half are preserved in fish," Mattick said. "So that means some of these sequences have remain unchanged during evolution for over 400 million years."

Mattick said that these sequences remained unchanged while protein-coding genes changed slowly through evolution.

"So whatever [these conserved regions] are, and whatever they're doing, evolution is really saying that they're critical to our biology in ways that we don't yet understand."

Mattick said some of the sequences overlapped with protein-coding genes, while some were outside genes. But all were strongly associated with genes involved in controlling development. "They're almost certainly regulatory," he said.

The blog post on RNA interference provides some further details on the role RNA plays in transcriptional gene regulation. Additional info on RNA splicing in dendrites is provided in the blog post on dendritic spines. But there's a lot more going on here...

For one thing, function specific proteins can be 'stockpiled' in 'cytoplasmic granules', as well as sent to these granules for destruction. From The Scientist - A New View of Translational Control (Dec. 5, 2005): "Researchers are rapidly uncovering so-called granules in the cytoplasm that cluster function-specific proteins for RNA storage, silencing, reuse, destruction, and perhaps even splicing. Apparently related to the well characterized maternal mRNA granules that jumpstart embryogenesis, these neighborhood processing centers serve important functions in adult cells, including shaping synaptic plasticity and responding to stress.
"I think we'll learn that how cells control the destruction and translation of messenger RNAs through these structures will be a fundamental part of the control of genetic expression," says Roy Parker at the University of Arizona in Tucson. In the past two years, Parker has found cytoplasmic structures containing mRNA decapping and degradation enzymes. These compartments first appeared to serve as an mRNA junkyard: Transcripts with shortened poly(A) tails, or those otherwise no longer needed were relegated here for destruction. Parker dubbed them processing bodies, or P-bodies.
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"It makes sense to have compartments for degradation. It's not just RNA randomly floating around with an enzyme happening to find it," says Keith Blackwell at Joslin Diabetes Center in Boston. But P-bodies may be more than just centralized paper shredders; they may store mRNA for later use. In September, when Parker and colleagues blocked translation in yeast cells by depriving them of glucose, the number of free-floating ribosome complexes known as polysomes decreased, and P-bodies grew in size as mRNAs went to them.5 But instead of being degraded, mRNAs accumulated. When glucose was restored, P-body size decreased and polysome number rose, suggesting that mRNAs were getting reused for translation. Reusing old mRNAs is likely more efficient and faster than making new ones, says John Rossi at the Beckman Research Institute of the City of Hope in Duarte, Calif.
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In neurons, mRNA granules seem to influence synaptic plasticity (the variability in a synapse's signal strength), which appears fundamental to memory formation and learning. Kosik and colleagues found that granules store translationally silent mRNAs in dendrites. When the cell is depolarized, Kosik hypothesizes that the granules release their mRNAs to polysomes, resulting in localized protein changes. "They make sure that translation is directed to specific locations and not in the wrong place," he explains. The importance of such systems is hard to predict, Kosik says: "We could be talking about a branch of biology as extensive and intricate as the study of how proteins are directed to their destinations." Parker notes that neuronal and maternal granules have proteins in common and says he's looking to see if neuronal granules also possess P-body proteins.

More recently, James H. Eberwine of U.Penn reports in his web page: We have shown that multiple mRNAs are localized in neuronal dendrites and have provided a formal proof of local mRNA translation in dendrites. Further, we have recently shown that the intracellular sites of localization and translation of these mRNAs can be altered by synaptic stimulation highlighting for the first time that in vivo translation of a mRNA can occur at different rates in distinct regions of a single cell (translation is primarily exponential in dendrites and linear in the cell soma).

More info on the work of Eberwine and colleagues is described in an article in The Medical News: RNA-associated introns guide nerve-cell channel production:In nerve cells, some ion channels are located in the dendrite, which branch from the cell body of the neuron. Dendrites detect the electrical and chemical signals transmitted to the neuron by the axons of other neurons. Abnormalities in the dendrite electrical channel are involved in epilepsy, neurodegenerative diseases, and cognitive disorders, among others.

Introns are commonly looked on as sequences of "junk" DNA found in the middle of gene sequences, which after being made in RNA are simply excised in the nucleus before the messenger RNA is transported to the cytoplasm and translated into a protein. In 2005, the Penn group first found that dendrites have the capacity to splice messenger RNA, a process once believed to only take place in the nucleus of cells.

Now, in the current study, the group has found that an RNA encoding for a nerve-cell electrical channel, called the BK channel, contains an intron that is present outside the nucleus. This intron plays an important role in ensuring that functional BK channels are made in the appropriate place in the cell.

When this intron-containing RNA was knocked out, leaving the maturely spliced RNA in the cell, the electrical properties of the cell became abnormal. “We think the intron-containing mRNA is targeted to the dendrite where it is spliced into the channel protein and inserted locally into the region of the dendrite called the dendritic spine. The dendritic spine is where a majority of axons from other cells touch a particular neuron to facilitate neuronal communication” says Eberwine. “This is the first evidence that an intron-containing RNA outside of the nucleus serves a critical cellular function.”

“The intron acts like a guide or gatekeeper,” says Eberwine. “It keys the messenger RNA to the dendrite for local control of gene expression and final removal of the intron before the channel protein is made. Just because the intron is not in the final channel protein doesn't mean that it doesn't have an important purpose.”

The group surmises that the intron may control how many mRNAs are brought to the dendrite and translated into functional channel proteins. The correct number of channels is just as important for electrical impulses as having a properly formed channel.

The investigators believe that this is a general mechanism for the regulation of cytoplasmic RNAs in neurons. Given the central role of dendrites in various physiological functions they hope to relate this new knowledge to understanding the molecular underpinnings of memory and learning, as well as components of cognitive dysfunction resulting from neurological disease.

So it really seems that each dendrite is remarkably self-contained, with its own mitochondrial energy supply, the ability to synthesize proteins and the ability to wharehouse proteins. And that the dendritic machinery can be dynamically reconfigured by the neuron based on synaptic activity - the mitochondria and the mRNA localization and translation sites can move from quiescent dendrites to active ones on demand.

Junk DNA has other secrets that are being discovered, as well - for example, RNA-guided mechanisms underlying genome rearrangement. From a recent article in ScienceDaily (May 21, 2009): Laura Landweber and other members of her team are researching the origin and evolution of genes and genome rearrangement, with particular focus on Oxytricha because it undergoes massive genome reorganization during development.

In her lab, Landweber studies the evolutionary origin of novel genetic systems such as Oxytricha's. By combining molecular, evolutionary, theoretical and synthetic biology, Landweber and colleagues last year discovered an RNA (ribonucleic acid)-guided mechanism underlying its complex genome rearrangements.

"Last year, we found the instruction book for how to put this genome back together again -- the instruction set comes in the form of RNA that is passed briefly from parent to offspring and these maternal RNAs provide templates for the rearrangement process," Landweber said. "Now we've been studying the actual machinery involved in the process of cutting and splicing tremendous amounts of DNA. Transposons are very good at that."
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They have concluded that the genes spur an almost acrobatic rearrangement of the entire genome that is necessary for the organism to grow.

It all happens very quickly. Genes called transposons in the single-celled pond-dwelling organism Oxytricha produce cell proteins known as transposases. During development, the transposons appear to first influence hundreds of thousands of DNA pieces to regroup. Then, when no longer needed, the organism cleverly erases the transposases from its genetic material, paring its genome to a slim 5 percent of its original load.

"The transposons actually perform a central role for the cell," said Laura Landweber, a professor of ecology and evolutionary biology at Princeton and an author of the study. "They stitch together the genes in working form." The work appeared in the May 15 edition of Science.

Listen to your junk man - he's singing!

Connecting the dots... "Let us begin anew"

2009-05-11T19:45:00.000-07:00

As I've learned more about bio-systems, starting from water molecules and working up to synapses and networks of neurons, I've come to appreciate how incredibly powerful and compact the molecular computing substrate that life is built on top of is. Our most powerful supercomputers take days to calculate how one protein molecule folds, when the simplest bacteria can perform millions of these operations in parallel in seconds. What these simulations give us, however, is insight into exactly what special characteristics each of the proteins has in all of the various shapes it can assume. Building up from this low level understanding, hopefully we will be able to understand what the larger-scale purpose is for each of the various signaling chains and genetic transcriptions that are taking place, and perhaps we may one day be able to model these complex molecular interactions using state machines and logic that allows us to achieve a functionally equivalent set of operations without having to precisely simulate cells at the molecular level.

There are a number of new approaches to try to get to this level of understanding.
On the BrainScience podcast mentioned in the previous post, Seth Grant provided some nice descriptions of the difference and connections between the "trendy" terms "genetics", "genomics" and "proteomics":
Genetics is the study of gene function or the function of the biology as revealed by genes, and typically involves the study of cells or animals where there has been a mutation or an abnormality introduced into a gene and as a result of that, the function of the cell or animal is changed. And, of course, the readers will understand this, but a mutation in a gene effectively means a change in the DNA sequence that encodes that gene.
Genomics is a different thing. Genomics is the study of the organization of all of the DNA or the 'genome'. And, of course, the genome encodes roughly 20,000 genes in mammalian systems, and therefore, when one is studying the genomics of man or mouse, we're studying all of the genes. Typically in genetics you might only study one gene at a time in many cases. So that gives you a sense of the difference between the large scale features of genomics and the somewhat small scale features of genetics.
Proteomics is the study of the sets of proteins, or all of the proteins that perform biological functions or are found in cells or tissues. "Proteome" is to proteins what "genome" is to genes. Again, proteome is dealing with large sets of molecules. In our case, we were particularly interested in the 'proteome' (or all of the proteins) found in synapses. But you might be interested in all of the 'proteome' of red blood cells, in other words, all of the proteins that are found in a red blood cell.

There's a very good paper called "The Many Facets of Natural Computing" that looks at some of the interaction networks that are active in biological systems. The paper was written by

Lila Kari, Department of Computer Science, University of Western Ontario, London, ON, N6A 5B7, Canada, lila@csd.uwo.ca

Grzegorz Rozenberg, Leiden Inst. of Advanced Computer Science, Leiden University, Niels Bohrweg 1, 2333 CA Leiden, The Netherlands, Department of Computer Science, University of Colorado at Boulder, Boulder, CO 80309, USA, rozenber@liacs.nl

Their copyright notice:
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee.
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[A]t the cell level, scientific research on organic components has focused strongly on four different interdependent interaction networks, based on four different “biochemical toolkits”: nucleic acids (DNA and RNA), proteins, lipids, carbohydrates, and their building blocks.

The genome consists of DNA sequences, some of which are genes that can be transcribed into messenger RNA (mRNA), and then translated into proteins according to the genetic code that maps 3-letter DNA segments into amino acids. A protein is a sequence over the 20-letter alphabet of amino acids. Each gene is associated with other DNA segments (promoters, enhancers, or silencers) that act as binding sites for proteins which activate or repress the gene’s transcription. Genes interact with each other indirectly, either through their gene products (mRNA, proteins) which can act as transcription factors to regulate gene transcription – either as activators or repressors –, or through small RNA species that directly regulate genes.

These gene-gene interactions, together with the genes’ interactions with other substances in the cell, form the most basic interaction network of an organism, the gene regulatory network. Gene regulatory networks perform information processing tasks within the cell, including the assembly and maintenance of the other networks. Research into modeling gene regulatory networks includes qualitative models such as random and probabilistic Boolean networks, asynchronous automata, and network motifs.(ref.)
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Proteins and their interactions form another interaction network in a cell, that of biochemical networks, which perform all mechanical and metabolic tasks inside a cell. Proteins are folded-up strings of amino acids that take three-dimensional shapes, with possible characteristic interaction sites accessible to other molecules. If the binding of interaction sites is energetically favourable, two or more proteins may specifically bind to each other to form a dynamic protein complex by a process called complexation. A protein complex may act as a catalyst by bringing together other compounds and facilitating chemical reactions between them. Proteins may also chemically modify each other by attaching or removing modifying groups, such as phosphate groups, at specific sites. Each such modification may reveal new interaction surfaces.

There are tens of thousands of proteins in a cell. At any given moment, each of them has certain available binding sites (which means that they can bind to other proteins, DNA, or membranes), and each of them has modifying groups at specific sites either present or absent. Protein-protein interaction networks are large and complex, and finding a language to describe them is a difficult task. A significant progress in this direction was made by the introduction of Kohn-maps, a graphical notation that resulted in succinct pictures depicting molecular interactions. Other approaches include the textual biocalculus, or the recent use of existing process calculi (π-calculus), enriched with stochastic features, as the language to describe chemical interactions. (ref.)

Yet another biological interaction network, and the last that we discuss here, is that of transport networks mediated by lipid membranes. Some lipids can self-assemble into membranes and contribute to the separation and transport of substances, forming transport networks. A biological membrane is more than a container: it consists of a lipid bilayer in which proteins and other molecules, such as glycolipids, are embedded. The membrane structural components, as well as the embedded proteins or glycolipids, can travel along this lipid bilayer. Proteins can interact with free-floating molecules, and some of these interactions trigger signal transduction pathways, leading to gene transcription. Basic operations of membranes include fusion of two membranes into one, and fission of a membrane into two. Other operations involve transport, for example transporting an object to an interior compartment where it can be degraded. Formalisms that depict the transport networks are few, and include membrane systems described earlier, and brane calculi.

The gene regulatory networks, the protein-protein interaction networks, and the transport networks are all interlinked and interdependent. Genes code for proteins which, in turn, can regulate the transcription of other genes, membranes are separators but also embed active proteins in their surfaces. Currently there is no single formal general framework and notation able to describe all these networks and their interactions. Process calculus has been proposed for this purpose, but a generally accepted common language to describe these biological phenomena is still to be developed and universally accepted. It is indeed believed that one of the possible contributions of computer science to biology could be the development of a suitable language to accurately and succinctly describe, and reason about, biological concepts and phenomena.

One of the problems that happens in science is that, in order to understand things deeply, scientists typically need to specialize in one specific area of research. As Daphne Koller, a professor of computer science at Stanford University, relates in an interview about her being awarded the first-ever ACM-Infosyst Foundation Award in Computing Sciences(ref.):
The world is very complex: people interact with other people as well as with objects and places. If you want to describe what’s going on, you have to think about networks of things that interact with one another. We’ve found that by opening the lens a little wider and thinking not just about a single object but about everything to which it’s tied, you can reach much more informed conclusions.

[Interviewer]Which was an insight you brought to the field of artificial intelligence…
Well, I wasn’t the only one involved. There had been two almost opposing threads of work in artificial intelligence: there were the traditional AI folks, who grew up on the idea of logic as the most expressive language for representing the complexities of our world. On the other side were people who came in from the cognitive reasoning and machine learning side, who said, “Look, the world is noisy and messy, and we need to somehow deal with the fact that we don’t know things with certainty.” And they were both right, and they both had important points to make, and that’s why they kept arguing with each other.

How did probabilistic relational modeling help settle the dispute?
The synthesis of logic and probability allows you to learn this type of holistic representation [of complex systems] from real-world data. It gives you the ability to learn higher-level patterns that talk about the relationships between different individuals in a reusable way.

You’ve begun applying your techniques to the field of biology.
Originally, it was a method in search of a problem. I had this technology that integrated logic and probability, and we had done a lot of work on understanding the patterns that underlay complex data sets. Initially, we were looking for rich data sets to motivate our work. But I quickly became interested in the problem in and of itself.

What problem is that?
Biology is undergoing a transition from a purely experimental science — where one studies small pieces of the system in a very hypothesis-driven way — to a field where enormous amounts of data about an entire cellular system can be collected in a matter of weeks. So we’ve got millions of data points that are telling us very important insights, and we have no idea how to get at them.

What have you learned about interdisciplinary collaboration from your work with biologists?
The important thing is to set up a collaborative effort where each side respects
the skills, insights, and evaluation criteria of the other. For biologists
to care about what you build, you need to convince them that it actually produces good biology. You have to train yourself to understand what things they care about, and at the same time you can train them in the methods of your community.

So it’s not just learning a new scientific language, but training yourself to respect a different research process.
It’s a question of finding people who are capable of learning enough of the other side’s language to make the collaboration productive.

This sentiment is echoed in numerous papers I've come across, as well as in the poetic conclusion of "The Many Facets of Natural Computing":
In these times brimming with excitement, our task is nothing less than to discover a new, broader, notion of computation, and to understand the world around us in terms of information processing.

Let us step up to this challenge. Let us befriend our fellow the biologist, our fellow the chemist, our fellow the physicist, and let us together explore this new world. Let us, as computers in the future will, embrace uncertainty. Let us dare to ask afresh: “What is computation?”, “What is complexity?”, “What are the axioms that define life?”.

Let us relax our hardened ways of thinking and, with deference to our scientific forebears, let us begin anew.

More...
Bulletin of the EATCS (2007): Machines of systems biology.
Nature (Sept. 2002): Cellular abstractions: Cells as computation
Cambridge University Press (1999): Computing and Mobile Systems - the π-Calculus
Information Technology in Systems Biology (Kohn Maps)
Developmental Biology (2007):The regulatory genome and the computer
Science Signaling (2004):Molecular interaction map of the mammalian cell
cycle control and DNA repair systems."
The Calculus of Looping Sequences for Modeling Biological Membranes"
IEEE (2007): A Uniform Framework of Molecular Interaction for an Artificial Chemistry with Compartments

"Once more into the breach, dear friends, once more!"

2009-05-04T21:25:00.000-07:00

The more I read about "Cognitive Computing", the more disenchanted I get with most of the work being done under this banner. There is an awful lot of hype going on here: everything from university researchers that claim how simple it is to create a silicon chip that accurately emulates millions of neurons and projects to create silicon prosthetics for some of the major centers in the brain to overly ambitious claims stating how close we are to getting computers to 'think' and thus to the resulting 'singularity'. Most 'cognitive computing' efforts seem to miss the point that there is more happening here than simple electrical signaling over a network. So coming across the following articles and podcast was like a breath of fresh spring air:

Complex Synapses Drove Brain Evolution:

ScienceDaily (June 9, 2008) — One of the great scientific challenges is to understand the design principles and origins of the human brain. New research has shed light on the evolutionary origins of the brain and how it evolved into the remarkably complex structure found in humans.

The research suggests that it is not size alone that gives more brain power, but that, during evolution, increasingly sophisticated molecular processing of nerve impulses allowed development of animals with more complex behaviours. The study shows that two waves of increased sophistication in the structure of nerve junctions could have been the force that allowed complex brains - including our own - to evolve. The big building blocks evolved before big brains.

Current thinking suggests that the protein components of nerve connections - called synapses - are similar in most animals from humble worms to humans and that it is increase in the number of synapses in larger animals that allows more sophisticated thought. "Our simple view that 'more nerves' is sufficient to explain 'more brain power' is simply not supported by our study," explained Professor Seth Grant, Head of the Genes to Cognition Programme at the Wellcome Trust Sanger Institute and leader of the project. "Although many studies have looked at the number of neurons, none has looked at the molecular composition of neuron connections. We found dramatic differences in the numbers of proteins in the neuron connections between different species".

"We studied around 600 proteins that are found in mammalian synapses and were surprised to find that only 50 percent of these are also found in invertebrate synapses, and about 25 percent are in single-cell animals, which obviously don't have a brain." Synapses are the junctions between nerves where electrical signals from one cell are transferred through a series of biochemical switches to the next. However, synapses are not simply soldered joints, but miniprocessors that give the nervous systems the property of learning and memory. Remarkably, the study shows that some of the proteins involved in synapse signalling and learning and memory are found in yeast, where they act to respond to signals from their environment, such as stress due to limited food or temperature change.

"The set of proteins found in single-cell animals represents the ancient or 'protosynapse' involved with simple behaviours," continues Professor Grant. "This set of proteins was embellished by addition of new proteins with the evolution of invertebrates and vertebrates and this has contributed to the more complex
behaviours of these animals.

"The number and complexity of proteins in the synapse first exploded when muticellular animals emerged, some billion years ago. A second wave occurred with the appearance of vertebrates, perhaps 500 million years ago."
...

There's an excellent podcast interview with Dr. Seth Grant at BrainScience - episode 51 that covers this work in more depth. Highly recommended!
Excerpt:
The ancestral proteins that are found in unicellular animals are the proteins that are found in more or less all of the different synapses in the brain of the mouse. The most recently evolved proteins - the vertebrate proteins - those are the ones that are most diverse in the brain regions of the mouse. So some of those proteins are very high, for example, in the frontal cortex, others might be high in the hippocampus, others might be high in the cerebellum; in other words, they're very variable like that.

So what that is telling us, then, and I'm just returning now to that ancient vertebrate synapse that arose before big brains, it tells us that when this 'big synapse' evolved, what the vertebrate brain then did as it grew bigger and evolved afterwards - it exploited the new proteins that had evolved into making new types of neurons in new types of regions of the brain.

In other words, we would like to put forward the view that the synapse evolution has allowed brain specialization - regionalization - to occur. And we know from many many studies that the regionalization of the brain - there's parts involved with learning, there's parts involved with fear, there's parts involved with some aspect of mood or so on, there's parts involved with motor function - that all appears to be built on the template of molecular evolution of the synapse. "

Journal References
Nature Neuroscience, 8 June 2008 Evolutionary expansion and anatomical specialization of synapse proteome complexity.
Emes RD, Pocklington AJ, Anderson CNG, Bayes A, Collins MO, Vickers CA, Croning MDR,
Malik BR, Choudhary JS, Armstrong JD and Grant SGN.

PubMed Abstract:Neurotransmitters drive combinatorial multistate postsynaptic density networks.
Coba MP, Pocklington AJ, Collins MO, Kopanitsa MV, Uren RT, Swamy S, Croning MD, Choudhary JS, Grant SG.

The mammalian postsynaptic density (PSD) comprises a complex collection of approximately 1100 proteins. Despite extensive knowledge of individual proteins, the overall organization of the PSD is poorly understood. Here, we define maps of molecular circuitry within the PSD based on phosphorylation of postsynaptic proteins. Activation of a single neurotransmitter receptor, the N-methyl-D-aspartate receptor (NMDAR), changed the phosphorylation status of 127 proteins.

Stimulation of ionotropic and metabotropic glutamate receptors and dopamine receptors activated overlapping networks with distinct combinatorial phosphorylation signatures. Using peptide array technology, we identified specific phosphorylation motifs and switching mechanisms responsible for the integration of neurotransmitter receptor pathways and their coordination of multiple substrates in these networks. These combinatorial networks confer high information-processing capacity and functional diversity on synapses, and their elucidation may provide new insights into disease mechanisms and new opportunities for drug discovery.

Infomax

2009-05-01T23:45:00.000-07:00

From "Modeling the Mind: From Circuits to Systems: section 1.2 "Sensory Coding" by Suzanna Becker.
"Several classes of computational models have been influential in guiding current thinking about self-organization in sensory systems. These models share the general feature of modeling the brain as a communication channel and applying concepts from information theory. The underlying assumption of these models is that the goal of sensory coding is to map the high-dimensional sensory signal into another (usually lower-dimensional) code that is somehow optimal with respect to information content. Four information-theoretic coding principles will be considered here: 1) Linsker's Infomax principle, 2) Barlow's redundancy reduction principle, 3) Becker and Hinton's Imax principle, and 4) Risannen's minimum description length (MDL) principle. Each of these principles has been used to derive models of learning and has inspired further research into related models at multiple stages of information processing.
...
The Infomax principle has been highly influential in the study of neural coding, going well beyond Linsker's pioneering work in the linear case. One of the major developments in this field is Bell and Sejnowski's Infomax-based independent Component Analysis (ICA) algorithm, which applies to nonlinear mappings with equal numbers of inputs and outputs (Bell and Sejnowkski, 1995).
...
The principle of preserving information may be a good description of the very earliest stages of sensory coding, but it is unlikely that this one principle will capture all levels of processing in the brain. Clearly, one can trivially preserve all the information in the input simply by copying the input to the next level up. Thus, the idea only makes sense in the context of additional processing constraints. Implicit in Linsker's work was the constraint of dimension reduction. However, in the neocortex, there is no evidence of a progressive reduction in the number of neurons at successively higher levels of processing.

Transcript of presentation by Ralph Linsker (IBM TJ Watson Research center)
(video, slides)
Lisker's presentation slot starts at the 50 minute mark in the video (aprox. 40% through). (Lisker's an excellent speaker, but his slides leave much to be desired!)

Slide 1. The search for organizing principals of brain function.

"My working belief is that one needs multiple organizing principles at multiple levels of the brain ranging from synapse up to hierarchies of areas within the neocortex and different areas apart from the neocortex. And my working belief is that the number of such high level organizing principles one might need is more than one but less than ten. And I'm going to talk about a couple of aspects of what these potential organizing principles might be, my special interest being at the level between cell and cortical maps.
...

Slide 2. Self-organization
It's striking to me sometimes how long it takes certain ideas to be put together, to be combined from different disciplines.
Turing had a wonderful paper, not the one for which he's most famous, but it's a seminal paper on morphogenesis in biology. 1952.
Hebb's idea that you've heard about dates from 1949.
An early puzzle in neuroscience arose from the work of Hubel and Wiesel, experimental work starting in 1960 which showed that, in cats and then later in monkeys one finds a layer of cells in which each cell responds selectively, preferrentially, to a local edge at some particular orientation. And that as you move across cortex, you find a pattern of the different preferred orientations. [see image at the top of this post] The puzzle was, "how does this come about"? They even found in monkey that this is present at birth, so it does not develop as a result of exposure to structured visual stimuli in that case.

What I found, my introduction to this area of self-organization in neural systems, was that if you combine the Hebb rule with short connections (known to exist in retina) and simply some random electrical activity that's at least locally correlated - so if one retinal ganglian cell is activate or seeing a bright spot, it's likely that at neighbouring cell is going to be seeing a bright spot as well, a portion of the same patch - that those ingredients alone can lead to orientation selective cells and also to their patterning within a cortical layer. By the way, that locally correlated electical activity prenatally was not known to exist at the time but was found a few years later experimentally.

Slide 3: Self-organization in cortical models
What you see [in the color image at the top of this post] is a pattern that I generated that, at the time, troubled me because it looked more complex than Hubel and Wiesel's pattern of orientation domains. The color coding reflects the preferred orientation of the cell, as represented by one of 5 colors here. And at the time, Hubel and Wiesel's patterns only referred to a coarser grained resolution - are you closer to a horizontal preference or closer to a vertical preference, for example. And those patterns looked rath, like fingerprints, meandering stripes.

When I came up with this I was troubled at first, but it turned out later that experimental work published after this came out by Blasdo and Salama revealled that the complexity of this pattern is, in fact, what's found in cortex, including the singularities where most or all of the colors meet at a point, which are now commonly called 'pinwheels'. Now that's a static view of the end of the optimization process using my model. Here's a movie thanks to Sirotia et al that uses a more elaborate version of this same model for self organization but is based on the same principles.

(Movie)

Staring from random orientation preferences (or lack of preference), you evolve using simple Hebbian-type learning rules to get this kind of resulting pattern.

Slide 4: Some higher-level properties that can result from Hebbian Learning
Now, that's well and good. What are some higher level properties that can result from Hebbian learning? To put it another way, if the Hebb rule for synapses is a good algorithm, what is it good for? What computational tasks is it good for? I'll illustrate with a couple of analogies that are really much stronger than metaphor - there's a mathematical base for them that's solid. But just to make the point quickly:
If you apply a Hebb rule to the synapses impinging on a given output cell, the cell can be regarded as a committee in which each member has a voting strength that's initially random, but he gets more votes each time his preference agrees with the final output of the committee.

What this does is it induces a consensus forming by the committee on a subset of issues that frequently come before it for consideration. So this committee becomes, for example, an orientation selective analyzing committee. On most questions that come to it, most local input patterns that come to it, it will have no strong opinion. Where there's an oriented edge, it will have a strong opinion, perhaps positive or negative.

So Hebb's rule induces a committee consensus and I extended this to the issue of an entire layer of cells that can interact in a competitive and cooperative manner, through lateral connections, and proposed what I call the "infomax" principle, which says:

Create a layer of cells connecting inputs to outputs.

The cells can compute any of a wide class of functions, subject to certain biological constraints.

Let it develop in such a way that its outputs convey maximum Shannon information on average about its inputs, subject to those biological constraints and costs.

the costs can be of different types: it could be types of allowed processing - how strong are the processors as computers, limited wire length, energy costs, and so forth.

It's an optimal encoding principle, and again, for a brief metaphor, imagine an organization now of human beings where no person is told what their job is explicitly, and in fact, no one is told what the goal of the entire organization is. All they're told is "you're going to receive masses of data each day, and your job is to write a summary in one page that captures as much Shannon information as possible about that input.

What each person will do is within the limits of their ability , find regularity, find patterns within that data so that they can capture it more concisely. And that, in essence, is what Infomax does.

It's been used in various ways, extensively for models of neural learning and development.

It leads to qualitative and quantitative agreement with experiment, especially in the first few stages of early visual processing.

It's the basis of Bell and Sejnowski's Independent Component Analysis method, which can reconstruct N statistically independent sources, given at least N linear combinations of them.

...

More...
Journal of vision article: Cone selectivity derived from the responses of the retinal cone mosaic to natural scenes
Andrei Cimponeriu (Georgetown Institute for Cognitive and Computational Sciences,
Georgetown University Medical Center):
Modeling the Development of Ocular Dominance and Orientation Preference Maps in The Primary Visual Cortex with The Elastic Net

"That which I cannot build, I do not truly understand" -- Richard Feynman

2009-04-23T20:30:00.000-07:00

In 2006, IBM Research hosted a series of lectures on Cognitive Computing, featuring presentations from some well-known researchers in neuroscience and cognitive computing. Videos of the lectures and the presentations that were given are available at http://www.almaden.ibm.com/institute/2006/agenda.shtml. A word of caution, however: as one person in the audience commented in a Q&A session after a panel presentation, a number of the presentations were more 'neuromythology' (i.e. bravado, marketing, speculation and wishful thinking) than neuroscience. I did learn a number of things from a few of the presentations, however, and will try to summarize the good stuff and ignore the rest in the next few posts.

The presentation by Henry Markram, EPFL/BlueBrain: The Emergence of Intelligence in the Neocortical Microcircuit (video) describes the Blue Brain project that Markram was director of at the time, which aimed to create a computer model of the neurons in a cortical column using a supercomputer to model each neuron and networking over 8000 of these supercomputer nodes together using MPI (Message Passing Interface - an industry standard messaging protocol for parallel computing). "Phase 1" of this work was completed in 2007.

Markram and his team's work was a technological Tour de Force, tackling some incredibly daunting challenges head on (ahem). For this post, I'd like to narrow the focus to some of the things I learned about spiking neuron models from Markram's presentation, and link some of these concepts to some of the things covered in previous posts. The images below are from Markram's presentation.

Re: Perkinjes and Granules and Schwanns, oh my...
Each neuron is unique, but when you look at a large number of them (as you need to do when you contemplate trying to model a 10,000 neuron cortical column!) you start to see similarities between the various neurons, enough so that you can classify them by shape:

Each of these classes of neurons can exhibit a wide variety of electrical behaviours:

Re: Ion Channels: gates in the cell wall and Receptors: getting the message across:

One of the factors that determines the electrical behaviour of a neuron is the combination of ion channels that it supports. You can determine which ion channels a particular neuron has 'implemented' by harvesting the neuron's cytoplasm, extracting the mRNA strands, performing reverse transcription and identifying all of the genes that code for ion channels.

Re: Will you remember me? I will remember you...
For all of the amazing fidelity and accuracy of the neuron models being used to create Blue Brain, there are a number of things that it doesn't tackle: e.g. the internal cellular biology of the neurons and the ability of a neuron to grow or modify its dendritic spines. At this stage ("Phase 1"), the Blue Brain project focused on creating a static snapshot in time of the neurons in the cortical column.

From the Blue Brain FAQ:

Q: How will you be able to replicate the complexity of neurons and neurotransmitter actions?

A: We have built 3D computer models of most of all the main types of neurons and can simulate their individual behaviors with great detail and very accurately. At this stage we can capture the complexity of the fast neurotransmitters very accurately as well with phenomenological models that we have built. A more difficult issue is the slow neurotransmitters and the neuromodulators as well as hormonal effects. These will take a while longer to model, but there is no major obstacle to this.

Q: What is the difference between cellular and molecular simulation?

A: The cellular level is a form of phenomenological model of the underlying molecular processes - a simplification - so it does capture many key processes, but molecular interactions are of course very complex and they keep neurons on a growth trajectory (real neurons are never biochemically stable), whereas in the simulations, neurons will tend to go back to a resting position when not activated. A very important reason for going to the molecular level is to link gene activity with electrical activity. Ultimately, that is what makes neurons become and work as neurons - an interaction between nature and nuture.

Two other questions that the FAQ doesn't address: What will "Phase 2" focus on and when will it get underway? A couple of news items provide a bit of a glimpse of what's next:

From IEEE Spectrum's TechTalk:
David Cremese, the manager of Deep Computing Programs at IBM Zurich, told me that the first phase of Markram's project is complete but that IBM intends very much to collaborate on future phases.

From TechnologyReport:
Technology Report has confirmed with IBM Switzerland that the Blue Brain project is waiting for Phase II funding from the Swiss Government. See the statement from Blue Brain project director Henry Markam ... as quoted by IBM Switzerland to Technology Report on January 19, 2009:

The funding:
There is a serious misconception that IBM somehow funded or donated to support the Blue Brain Project. The BBP project is funded primarily by the Swiss government and secondarily by grants and some donations from private individuals. The EPFL bought the BG, it was not donated to the EPFL. It was at a reduced cost because at that stage it was still a prototype and IBM was interested in exploring how different applications will perform on the machine - we were a kind of beta site.

The Collaboration:
The Blue Brain Project is a project that I conceived over the past 15 years. I chose the name because of the Blue Gene series which is a fantastic architecture for brain simulations. When we bought the BG, we also had to make sure that we have the computer engineering and computer science expertise to run the machine and optimize all the programs. So BG came to us with IBM’s full support as a technology partner. This component of the collaboration is invaluable to the Project and will continue and grow as long as we have a Blue Gene or other architectures from IBM. This
is by far the major component of the collaboration.

IBM Research at T.J. Watson, also contributed a postdoc that was sent to work with us at the EPFL and assigned a researcher at Watson to work on some computational neuroscience tasks. The research and term assigned to these postdocs is done, a success and published. Actually, the term expired almost a year ago, and the IBM postdoc, Sean Hill, actually transfered and is now an employee of the BBP and not IBM. The researcher at TJ Watson worked on a specific problem of collision detection between the axons and dendrites and this is done very well and already published. Although very important projects and contributions, this is a small part of the BBP which is carried out at the EPFL and involves, neuroscience, neuroinformatics,
vizualization, and a vast spectrum of computational neuroscience.

BBP needs BG’s to continue the project. The architecture is perfect for brain simulations. When we manage to get our funding to buy the next BG/P finalized, we will start Phase 2 and that will of course involve the basic (and most significant) technology collaboration, and most likely also many new collaborations on specific research targeted topics where we see that IBM can, and would like to, contribute. So this is an intermediate phase while we get ready for phase 2 - molecular level modeling.

BBP sees IBM as a key partner in the BBP and I do think that IBM also sees the value in the BBP. We are getting ready for Phase 2, but it has not started until we get the next BG series.

One further hint as to what Markram might be thinking about for Phase 2 is alluded to in an aside Markram made on "Microcircuit plasticity" 48 minutes into his presentation (slide 56):
"We patched 6 cells, and we see how they're connected so we can define the circuit [they make]. Now we take the pipettes out and we wait 12 hours, and we re-patch it. And what we found is that the circuit was different. Not only after 12 hours but actually after 4 hours.

And just to show you how much inertia there is in the current scientific paradigm, [Science magazine] said that this was not interesting. It will come out in PNAS in another 2 months.". (aside: some interesting comments on this work here, including a reference to the PNAS paper). Markram continued: So we do these recordings, and we puff glutamate now [into the circuit] - we actually activate the circuit. We can't still put intelligent stimulus, but we activate the circuit. And when you activate the circuit, here you can see that you have connections appearing and disappearing. This is potentially the substrate that Nobelist Gerry Edelman could use in all kinds of restructuring of the circuitry. Over a 4 hour period you can still see the circuitry is dynamically rewiring. For 50 years we've studied only how synapses are getting stronger and weaker, not how the circuit restructures itself.

This, to me, is one of the most important "forward looking" things Markram focused on during the talk, because it goes beyond the idea of modeling the brain as a static 3D electrical network made up of ion channels and opens the door to the idea that the protein synthesis, dendritic spine growth and neuron rewiring that have been observed to happen with real neurons are also important factors in how the brain works. I hope this is a hint of things to come in Phase 2!

A couple of thoughts occurred to me was as I was going through the presentation. One was that what neurons are really designed to do is to precisely send chemical signals to a specific set of other cells. Instead of releasing chemical messenger molecules out into the body where any cell can pick them up, neurons extend long appendages that deliver the chemical messages right to the front door of the cells that it wants to receive the messages. How does it know which cell(s) to grow the appendages towards? One of the ways the body uses to govern how cells grow during development ('morphobiology') is through the use of chemical gradients that trigger genetic transcription factors at certain points along the gradient. I wonder what chemical (or 'electro-chemical?') gradients exist in the space between neurons that could guide this growth?

The second thought occurred to me after seeing the variety of different types of action potentials that the neurons can generate: perhaps the 'neural code' that these bursts of spikes transmit is not simply used to pass on information that has been received by the senses and processed by other regions in the brain - perhaps it is a set of instructions to the cells that this information is being passed on to that help these cells retain and process this information by generating the appropriate set of proteins at exactly the right time - an electrical stimulus to trigger the necessary chemical chain reactions within the cytoplasm of the cell. This would link up the work done by Dr. Fields et. al at the cellular and molecular level with the with work being done at the connectionist / action potential modeling level... Time to fire up Google and see what work has been done in this area!

Synchronicity - spatio-temporal spiking neuron models

2009-04-13T20:18:00.000-07:00

The previous post began with a slogan pertaining to Hebbian learning that was coined by Donald Hebb: "Cells that fire together, wire together". A number of papers have been appearing in recent years that extend this idea further - that pulses that coincide are actually one of the most important ways that the brain transmits information. This concept appears to be a natural consequence of Hebbian learning: the brain adapts its network of synaptic connections by pruning those connections where the incoming signals are not correlated with other signals coming into the neuron and reinforces those where this type of coincidence does occur. It is doing this for a reason - to establish the 'right' set of connections and synaptic weights in order to associate one input or one set of inputs with another. This type of correlation between events has been proposed as being what knowledge itself is made of and as the basis for some of the key aspects of cognition and symbolic thought (ref.).

Not everyone agrees with this idea that the relative timing of spikes is what is used to carry information, however. There are many researchers that focus on trying to understand the 'neural code' that is used by the brain to send information from one neuron to another. Claude Shannon's Information Theory is often used as a mathematical framework to try to determine how many 'bits of data' are sent from one neuron to another and the efficiency of the information transferred from one neuron to the next. Researchers who favour this approach generally model the transmission of spikes from one neuron to the next using "rate coding" (a.k.a. "frequency coding") models. These models are based on the idea that neurons will only reach the threshold needed to generate a spike and send it to the next neuron when the number of spikes it receives exceeds in a given time period exceeds some value.

Although information theory has proven to be a useful way to gain insight into the lower levels of vision processing (e.g. Ralph Linsker's Infomax principle), it doesn't seem to me that constraining the theory of how neurons interact so that it can be described using the math of Information Theory is helpful - the concept of 'how much information' is transferred from one neuron to the next is determined primarily by which neuron the spike is sent to; information theory is not the right tool to approach this with. Using the mathematical framework of information theory narrows the focus down to things like the frequency of the spikes that are sent from one neuron to the next, and researchers end up making the wrong type of simplifications in order to achieve this - things like combining both the efficiency of the synapse and the 'frequency' of the incoming spikes into a single 'synaptic weight', and ignoring the idea that the network of neurons is constructed in such a way as to enable coincidence detection. A different way of measuring information is needed - one that takes into account the 100's, 1000s or 10,000s of connections each neuron can send that spike to, whether the spike is used to inhibit or excite the downstream neuron, the topology of the connections between groups of neurons, the fact that neurons can rewire themselves dynamically, the role that neurotransmitters play, etc.

The rate coding model aligns well with the popular Computer Science approaches to implementing neural networks in software - time does not play a significant role in the way these models operate. Training data is used to ensure that the weights converge to whatever is required in order to map the input data to the expected output data in the training set. What these software models completely ignore is the idea that the input signals in the brain are sent as neuronal spikes, and that the correlation between spikes is what causes the synapses to either grow stronger or weaker. Rate coding attempts to bridge this gap by noting that spikes from a neuron often are generated in a repetitive series - a spike train - and that the frequency of these spikes will tend to drive the receiving neuron beyond its signaling threshold. The relative density of spikes over a given time interval, the thinking goes, is what matters; the timing of the individual spikes is not important. Rate coding also glosses over the fact that neurons do not have spikes arriving at a constant rate - they arrive sporadically and in bursts (ref.)

The rank coding model (a.k.a. Delay coding), on the other hand, is based on the idea that sensory neurons (e.g. in the retina and inner ear) will respond to more energetic input signals by generating a spike earlier, that this generated spike will arrive at the downstream neuron earlier than other spikes and will thus have a higher impact or 'ranking' relative to later incoming spikes as a result. The rank coding model notes that there are some specific examples where the only way the brain can respond quickly enough to an incoming stimulus (e.g. a noise or an image) is if a single neuron were to respond to the initial spike that was sent from the neuron in the eye or ear. Software models of rank-encoding methods and "liquid state machines" are starting to appear (e.g. SpikeNET Technology ) which offer capabilities that outperform standard software neural networks for certain appliations. These are the leading edge of a "third generation" of software models of neural networks, which look very promising.

From Networks of Spiking Neurons: A New Generation of Neural Network Models by Thomas Natschläger (December 1998):

The First Generation of Models
If one wants to understand how the nervous system computes a function one has to think about how information about the environment or internal states is represented and transmitted. The fact that the shape of an action potential is always the same one can exclude the possibility that the voltage trajectory of an action potential carries relevant information. Thus a central question in the field of neuroscience is how neurons encode information in the sequence of action potential they emit. In this article we characterize neural network models by the assumptions about the encoding scheme.

1943 McCulloch and Pitts proposed the first neuron model: the threshold gate. The characteristics of their model was that they treated a neuron as a binary device. That is they distinguished only between the occurrence and absence of a spike. The threshold gate is used as building block for various network types including multilayer perceptrons, Hopfield networks and the Boltzman machine. It turned out that the threshold gate is a computational powerful device. That is one can compute complex functions with rather small networks made up of threshold gates. From the theoretical point of view the threshold gate is a very interesting model but it is unlikely that real biological systems use such a binary encoding scheme. A prerequisite for such a binary coding scheme is a kind of global clocking mechanism but it is very unlikely that such a mechanism exists in biological systems.

The Second Generation
Another possibility is that the number of spikes per second (called the firing rate) encodes relevant information. This idea lead to a model neuron known as sigmoidal gate. The output of a sigmoidal gate is a number which is thought to represent the firing rate of the neuron. There exists a huge amount of literature which discusses in detail all aspects of this kind of neural network models. We just want to note that networks of sigmoidal gates can in principle compute any analog function and that along with this type of models the question of learning in neural networks was intensively investigated for the first time.

...
The Third Generation: Networks of Spiking Neurons (SNN)
...[Results] from experimental neurobiology gave rise to a new class of neural network models where one also incorporates the timing of individual spikes. Thus time plays a central role in SNNs whereas in most other neural network models there is even no notion of time.

The standard Computer Science neural networks are based on the second generation of models, and have been found to be useful in applications including text recognition, speech recognition and stock market prediction. Software implementations of the third generation of models are starting to appear. They are based on more accurate computer representations of biological neural networks and will hopefully open up new types of software applications in areas such as machine vision and robotics.

References

Rate Codes and Shannon's Information Theory
Information theory and neural coding - Alexander Borst and Frédéric E. Theunissen
Energy-efficient interspike interval codes
Neural coding and decoding: communication channels and quantization
Introduction: statistical and machine learning based approaches to neurobiology - Shin Ishii
Nara Institute of Science and Technology
Information Theory and Systems Neuroscience
Entropy as an Index of the Informational State of Neurons

Rank Coding and Temporal Coding
SpikeNET - Scientific papers by Simon Thorpe & colleagues
Publications related to SpikeNET
The Neural Basis of Temporal Processing
Temporal Coding and Analysis of Spike Sequences
Synfire Chains and Cortical Songs: Temporal Modules of Cortical Activity

Spike-based Neural Network Models
Networks of Spiking Neurons: A New Generation of Neural Network Models - Thomas Natschläger
Computing with spikes - Wolfgang Maass

Neurotrophins

2008-09-07T11:53:00.000-07:00

In 1949, Canadian psychologist Donald Hebb proposed that "When an axon of cell A is near enough to excite cell b or repeatedly and consistently takes part in firing it, some growth process or metabolic changes take place in one or both cells such that A's efficiency, as one of the cells firing B, is increased". (ref.) This idea is captured in the slogan 'Cells that fire together wire together'. A special set of molecules called neurotrophins play an important role in this. From Joseph LeDoux's book The Synaptic Self: When an action potential occurs in a postsynaptic cell, neurotrophins are released from the cell and diffuse backward across the synapse, where they are taken up by presynaptic terminals. Under the influence of neurotrophins, the terminals begin to branch and sprout new synaptic connections. Since only those presynaptic cells that were just active (that just released transmitter) take up the molecules, only they sprout new connections. activity thus induces growth, and the growth that occurs is restricted to the active terminals.
In addition to this role in the active construction of ciruits, neurotrophins are also involved in synapse selection. The natural fate of may cells during development is an early exit. So-called programmed cell death is one of the regressive events that help shape the final pattern of connectivity. Cell death is prevented if a presynaptic terminal receives a lifes-sustaining shot of neurotrophins from it postsynaptic partner. The survival rate of neurons is in this way regulated by the limited availability of neurotrophins. Only those cells that compete successfully for neurotrophins (those that are active) survive. In the presence of neurotrophins, the surviving terminals (those that were active) alsso begin to sprout new connections. Selection can be a step along the path toward activity-instructed growth -- in other words, selection and instruction are partners in synaptic development.
The image at the top of this post shows undifferentiated cells extending neuronal processes after exposure to neurotrophin delivered from hydrogel coated neural prosthetic devices. This idea of using neurotrophins to efficiently 'wire up' neurons with prosthetic devices is quite intriguing. Let's take a closer look at what neurotrophins are and how they work...

From the Society for Neuroscience article Neurotrophic Factors :
Recent research shows that neurotrophic factors are:

Present in early development of the nervous system and are responsible for the initial growth and development of neurons in the peripheral and central nervous systems.

Released by target tissue of a growing neuron and can determine whether a neuron reaches its target during development; neurons which do not reach the target die.

Capable of making damaged neurons regrow their processes in a test tube and in animal models and, thus, represent exciting possibilities for reversing devastating disorders, including Alzheimer's disease, Parkinson's disease and amyotrophic lateral sclerosis (ALS), also known as Lou Gehrig's disease.

...
Neurotrophic factors, produced by several body tissues including muscle, act by attaching to receptors on the tips, or nerve terminals, and on the cell body -- which contains the nucleus -- of neurons. The signal can then be carried through the axon, the neuron's elongated fiberlike extension, which can be as long as a yard, to the cell body where it tells the cell what to do.
Thus far, scientists have identified several neurotrophic factor receptors -- which also may be potential targets for therapy. A receptor called trk is required for the action of nerve growth factor (NGF), the first neurotrophic factor, which was discovered 40 years ago. NGF affects primarily neurons using the neurotransmitter acetylcholine in the basal forebrain, sensory neurons and sympathetic neurons that regulate organs such as the heart and lungs. Relatives of trk are receptors for other neurotrophic factors -- trkB seems to be a receptor for brain-derived neurotrophic factor; and trkC for neurotrophin-3.
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In the brain, a neurotrophic factor is released by a neuron or a support cell, such as an astrocyte, and binds to a receptor on a nearby neuron. This binding results in the production of a signal which is transported to the nucleus of the receiving neuron where it results in the increased production of proteins associated with neuronal survival and function.

From Developmental Biology online" by Scott F. Gilbert:
The neurotrophin family consists of four members: nerve growth factor (NGF), brain derived neurotrophic factor (BDNF), neurotrophin 3 (NT-3), and neurotrophin 4 (NT-4). Each provides some survival activity on nervous tissue. As mentioned in the text, the final number of neurons innervating a particular organ is attained by thinning the population of neurons through programmed neuronal death. Here, neurotrophic factors secreted by cells in the target field protect the neurons from apoptosis (Korsching, 1993; Lewin and Barde, 1996). Thus, the final number of neurons innervating a target reflects the availability of neurotrophins. The ability of particular neural subsets to respond only to particular neurotrophins can explain the losses of certain peripheral sympathetic neurons in NGF-knockout mice, the deficiency of sensory neurons in BDNF knockout mice, the lack of proprioceptive neurons in NT-3 knockout mice, and the deficiency of particular sensory neurons in NT-4 knockout mice. Neurotrophins also play roles in regulating neuronal plasticity and in regulating the number of neural progenitor cells.

Neurotrophin receptors

There are two classes of neurotrophin cell-surface receptors. The p75 receptor (also known as the low-affinity neurotrophin receptor, LANR) is common to all members of the neurotrophin family. The high affinity receptors (having binding constants on the order of 10-11) include receptor tyrosine kinase proteins TrkA, TrkB, and TrkC. These receptors have different specificities for different members of the neurotrophin family TrkA is the receptor for NGF, trkB is the receptor for BDNF and NT-4, and trkC is the receptor for NT-3. However, NT-3 can also bind to trkA and trkB, but with lower affinity than to trkC, and with lower affinity than the primary ligands for these receptors. Similarly, NT-4 also binds to trkA but with lower affinity.

In addition to these "classical" receptors, the issue is complicated by the existence of isoforms of trkB and trkC, which lack the cytoplasmic tyrosine kinase catalytic region (Barbacid, 1995). These receptors are found throughout the developing body as well, and it is not known if these noncatalytic forms of the receptors act as agonists or inhibitors.

All four neurotrophins also bind to the low affinity nerve growth factor receptor, p75. The p75 receptor belongs to the tumor necrosis factor receptor family and was the first identified neurotrophin receptor (Johnson et al; 1986). This receptor will bind the neurotrophins, but it has no cytoplasmic tyrosine kinase domain (Chao and Hempstead, 1995; Greene and Kaplan, 1995; Segal and Greenberg, 1996). The roles of this receptor are controversial, as it may also be involved in either promoting or downregulating the response to the neurotrophin. P75 may function to increase the affinity of the trk receptors for their respective neurotrophins, or it may bind the neurotrophins and prevent them from binding to the high affinity receptors. Although it does not have a catalytic intracellular tyrosine kinase domain, it is capable of mediating the neurotrophin signals. The ligand binding of p75 increases the high-affinity TrkA binding sites, enhances TrkA autophosphorylation and selectivity for neurotrophin ligands (Kaplan and Miller, 1997). P75 also increases intracellular ceramide levels and further activates NFk B transcription factor (Carter et al., 1996) and JNK kinase (Casaccia-Bonnefil et al., 1996) independently of tyrosine kinase activity. Conversely, TrkA activation can inhibit p75-mediated signaling, but the mechanism of this inhibition is unclear (Kaplan and Miller, 1997).

The TrkA neurotrophin receptor has been linked to human diseases. The TrkA gene was originally described as an oncogene in colon cancer (Martin-Zanca et al., 1986) and its translocations are common in papillary thyroid carcinoma (Bongarzone et al., 1989). Recently, a mutation in the TrkA gene was found to cause congenital insensitivity to pain with anhidrosis (CIPA) syndrome (Indo et al., 1996) that closely resembles the phenotype of the TrkA -deficient mice. No disease associations have been described either for the TrkB gene, or the genes for p75NTR or any of the neurotrophins.

From the abstract for Neurotrophin secretion from hippocampal neurons evoked by long-term-potentiation-inducing electrical stimulation patterns by Annette Gärtner and Volker Staiger: The neurotrophin (NT) brain-derived neurotrophic factor (BDNF) plays an essential role in the formation of long-term potentiation (LTP). Their study found that instantaneous secretion of BDNF is evoked by the same type of action potentials that induce LTP, whereas stimuli that induce Long Term Depression of a neuron do not induce secretion of BDNF.

Recently, further studies have provided additional details on the workings of BDNF. From Backpropagating Action Potentials Trigger Dendritic Release of BDNF during Spontaneous Network Activity by Nicola Kuczewski et. al: We found that spontaneous backpropagating action potentials, but not synaptic activity alone, led to a Ca²⁺-dependent dendritic release of BDNF-GFP. Moreover, we provide evidence that endogenous BDNF released from a single neuron can phosphorylate CREB (cAMP response element-binding protein) in neighboring neurons, an important step of immediate early gene activation. Therefore, together, our results support the hypothesis that BDNF might act as a target-derived messenger of activity-dependent synaptic plasticity and development.

An article in Nature (The Yin and Yang of neurotrophins" by Bai Lu, Petti T. Pang & Newton H. Woo") provides insight into the role played by neurotrophins and how BDNF is synthesized in neurons. From this article, it appears that in some cases, instead of BDNF being released by the dendrites and promoting axonal branching, it instead can be released by the axon and promotes the growth of additional dendritic spines.

The following picture is a schematic showing the synthesis and sorting of brain-derived neurotrophic factor (BDNF) in a typical neuron.

First synthesized in the endoplasmic reticulum (ER) (1), proBDNF (precursor of BDNF) binds to intracellular sortilin in the Golgi to facilitate proper folding of the mature domain (2). A motif in the mature domain of BDNF binds to carboxypeptidase E (CPE), an interaction that sorts BDNF into large dense core vesicles, which are a component of the regulated secretory pathway. In the absence of this motif, BDNF is sorted into the constitutive pathway. After the binary decision of sorting, BDNF is transported to the appropriate site of release, either in dendrites or in axons. Because, in some cases, the pro-domain is not cleaved intracellularly by furin or protein convertases (such as protein convertase 1, PC1) (3), proBDNF can be released by neurons. Extracellular proteases, such as metalloproteinases and plasmin, can subsequently cleave the pro-region to yield mature BDNF (mBDNF) (4). MMP, matrix metalloproteinase.

The last picture in this post (also from (The Yin and Yang of neurotrophins" by Bai Lu, Petti T. Pang & Newton H. Woo") shows the role BDNF plays in promoting the growth of additional dendritic spines and how its absence results in the retraction of dendritic spines:

a) Molecular cascade of brain-derived neurotrophic factor (BDNF) processing in late-phase long-term potentiation (L-LTP). In response to theta-burst stimulation (TBS), tissue plasminogen activator (tPA) is secreted into the synaptic cleft and cleaves the extracellular protease plasminogen to yield plasmin (1). Plasmin then cleaves proBDNF (the precursor of BDNF, which is released in an activity-dependent manner), yielding mature BDNF (mBDNF) (2). mBDNF binds to TrkB and triggers a series of downstream signalling pathways to induce LTP (3). During the maintenance stage of LTP, mBDNF might be generated by intracellular cleavage after postsynaptic transcription and translation (4). By contrast, proBDNF secreted extracellularly remains uncleaved after low-frequency stimulation (LFS). Uncleaved proBDNF binds to the p75 neurotrophin receptor (p75NTR) (5) to facilitate the induction of long-term depression (LTD), possibly through the regulation of NMDA (N-methyl-D-aspartate) receptor NR2B subunit expression. b) Morphological alterations in synapses induced by pro- and mature BDNF. Left, BDNF–Trk signalling might be an active mechanism that converts activity-induced molecular signals into structural plasticity, contributing to synapse formation. Right, proBDNF–p75NTR signalling might be important in translating activity-dependent signals into negative modulation of structural plasticity, contributing to synapse retraction.

Some good progress is being made on using neurotrophins to encourage neurons to integrate with medical implants. From EurekAlert (with thanks to the Biosingularity blog): Plastic coatings could someday help neural implants treat conditions as diverse as Parkinson’s disease and macular degeneration.

The coatings encourage neurons in the body to grow and connect with the electrodes that provide treatment.Jessica O. Winter, assistant professor of chemical and biomolecular engineering at Ohio State University described the research Thursday, August 21 at the American Chemical Society meeting in Philadelphia. She is also an assistant professor of biomedical engineering.

Worldwide, researchers are developing medical implants that stimulate neurons to treat conditions caused by neural damage. Most research focuses on preventing the body from rejecting the implant, but the Ohio State researchers are focusing instead on how to boost the implants’ effectiveness.

“We’re trying to get the nerve tissue to integrate with a device — to grow into it to form a better connection,” Winter said.

She and her colleagues are infusing water-soluble polymers with neurotrophins, proteins that help neurons grow and survive.

They are combining different polymers, some shaped like tiny spheres and fibers, to create composite coatings that release neurotrophins in a steady dose over time. The coatings also give nerves a scaffold to cling to as they grow around an implant.

The researchers coated two kinds of electrodes — one, a flat electrode used in retinal implants, and the other a cylindrical electrode array used in deep brain stimulation. The first is being used in experimental treatments for macular degeneration, while the second holds promise for suppressing tremors in people who have Parkinson’s disease. So far, however, it appears that the neurite growth achieved in this manner is short-lived. More info on this is available here.

A Rush of Blood to the Head - How neurons tell blood vessels where the action is

2008-08-30T21:04:00.000-07:00

One of the reasons that neuroscience has taken off over the last decade is the emergence of functional Magnetic Resonance Imaging as a tool to non-invasively watch the living human brain in action. But fMRI scans can't directly detect neurons firing - instead, they monitor where blood is flowing in the brain. The brain somehow directs the body's vascular system to bring blood to just those regions of the brain that need it, a "Just In Time" marshalling of resources. And this happens not just in the brain but throughout the body, under direction from the nervous system.

Basically, in order to get blood to flow to a specific region of the body, the diameter of the blood vessels in this region need to increase ("vasodilation"). This reduces the blood pressure and, since liquids always flow from regions of high pressure to regions of low pressure, blood moves into the area of the brain that has dilated blood capilleries. The fMRI detects the fact that there are more oxygen-carrying red blood cells in the area because haemoglobin is high in iron (details). But, how do neurons tell blood vessels what to do in the first place?

From Medical News Today (with thanks to the Marathon of Life blog): 06 Jan 2007 - Scientists at the University of Vermont have clarified the cellular process responsible for signaling regional blood flow changes in the brain, thereby uncovering possible causes for such disorders as stroke, migraine, and Alzheimer’s disease. The study was published November 1, 2006 in the prestigious journal Nature Neuroscience.

To function properly, the brain needs to receive an uninterrupted supply of oxygen and glucose, which is provided through an intricate network of blood vessels in the brain. Different parts of the brain are engaged by every activity, such as analytical thought, piano playing, seeing, hearing, walking, and these regions then require a rapid elevation of blood flow to meet the increased metabolic needs of the relevant brain cells (neurons). Though this cellular activity can be visualized in modern-day functional brain scans, the mechanisms by which these neurons signal blood vessels to dilate and increasing blood flow remain largely unknown, and are central to understanding brain function.

The diameter of blood vessels in the brain can be modulated by extracellular potassium, a common element present inside and outside all cells of the body. Such modulation of vessel diameter permits changes in blood flow to occur in the brain, as well as in other organs and tissues. With this knowledge, lead study author Mark Nelson, Ph.D., professor and chair of pharmacology at the University of Vermont, set out to determine whether the diameter of cerebral blood vessels in the brain could be modulated under physiological conditions by external potassium ions. To accomplish this, he and his research team studied the communication that takes place between neurons and blood vessels in mouse and rat brains.

The research team discovered early on that neuronal activity appeared to be communicated to the blood vessels through intermediary cells known as astrocytes. Astrocytes, which comprise about half the brain, had not been thought to play an active role in brain processes, and were thought to serve as the "glue" of the brain. One end of an individual astrocyte forms extensive contacts with thousands of neurons, while the other end surrounds and encases blood vessels. In this way, astrocytes are capable of integrating information from a large number of neurons and translating this information into distinct physiological outcomes, including modulation of blood flow.

The research team found that a wave of calcium ions moves through the astrocyte from the point of contact with the active neuron(s) to the 'endfeet' of the astrocyte that encase the blood vessel. This increase in calcium at the endfeet activates a calcium-sensitive protein, known as a potassium (BK) channel, which permits potassium ions to pour out of the astrocytes onto the adjacent muscle cells in the brain artery. The diameter of a blood vessel is controlled by smooth muscle cells in the walls of the blood vessel, which in turn are controlled by 'inward rectifier' potassium ion channels. When there is a small elevation of external potassium, the activity of these channels increases, causing smooth muscle cells to become less excitable, resulting in relaxation of the cells, dilation of vessels, and hence an increase in local blood flow. Activation of a single astrocyte endfoot was found to be sufficient to dilate a blood vessel.

This ability to direct where the blood flows is not limited to just the brain. From Dr. Joseph LeDoux's book "The Emotional Brain": According to [Walter] Cannon's hypothesis, the flow of blood is redistributed to the body areas that will be active during an emergency situation so that energy supplies, which are carried in the blood, will reach the critical muscles and organs. In fighting, for example, the muscles will need energy more than the internal organs (the energy used for digestion can be sacrificed for the sake of muscle energy during a fight). The emergency reaction, or "fight or flight response," is thus an adaptive response that occurs in anticipation of, and in the service of, energy expenditure, as is often the case in emotional states.
As always, Nature's engineering prowess is truly awe inspiring!

Even though fMRI is a huge advance in our ability to peer inside the inner workings of the mind, it still has some severe limitations. There's actually a 1-2 second delay between the time a neuron fires and the time the blood vessels react, which means that the fMRI has lousy time resolution. From "The Movie in Your Head" by Christof Koch (Scientific American Mind Vol 16, Number 3, 2005): If, in fact, changing coalitions of larger neuron groups are the neuronal correlates of consciousness, our state-of-the-art research techniques are inadequate to follow this process. Our methods either cover large regions of the brain at a crude temporal resolution (such as fMRI, which tracks sluggish power consumption at timescales of seconds), or we register precisely (within one millisecond) the firing rate of one or a handful of neurons out of billions (microelectrode recording). We need fine-grained instruments that cover all of the brain to get a picture of how widely scattered groups of thousands of neurons work together.

Block Rockin' Beats - Glutamate Excitation and GABA Inhibition

2008-06-16T20:31:00.000-07:00

I'm currently reading Joseph LeDoux's excellent book "Synaptic Self" - I highly recommend it. Chapter 3 of the book - "The Most Unaccountable Machinery" - does a splendid job of covering the basic working mechanisms of neurons, axons, dendrites and synapses, as well as the history behind some of the most important discoveries in neurobiology. The section covering inhibition was particularly enlightening for me, so I'd like to use this post to capture the key points on inhibition and the roles of Glutamate and GABA.
In a previous post (Neurotransmitters - molecular messages), the following definition of GABA was quoted from another excellent (and free!) book: "Discovering the Brain" by Sandra Ackerman: GABA (gamma-aminobutyric acid) often acts as a fast synaptic transmission inhibitor. Unlike dopamine or serotonin, which have diverse roles, GABA consistently acts as an “off” signal; the cerebellum, retina, and spinal cord all use this transmitter to inhibit signals, as do many other parts of the brain and nervous system. GABA's inhibitory effect comes about in the following way: the transmitter opens a channel in the membrane through which negatively charged chloride ions can enter the cell. This influx hyperpolarizes the cell and makes it less likely to be excited by incoming stimuli. GABA receptor sites show some tendency to bind barbiturates and the “minor tranquilizers,” the benzodiazepines. Curiously, the presence of GABA in low concentrations enhances the binding of benzodiazepines to receptor sites. This pattern indicates that GABA and the benzodiazepines cannot be competing for exactly the same sites. Instead, an array of recent studies have yielded the view that the GABA receptor site is in fact a multifunctional set of proteins that contain the chloride ion channel and distinct subsites for binding of benzodiazepines, other tranquilizers such as barbiturates, and GABA itself.
Unlike GABA, Glutamate (the 'G' in MSG) is an excitatory neurotransmitter. Dr. LeDoux refers to Glutamate and GABA as "The Chemical Brothers" (hence this post's title :) )

From Synaptic Self: Inhibition is a very useful device in neural circuits. It adds termendously to the specificity of information processing, filtering out random excitatory inputs, preventing them from triggering activity. Only if the excitatory inputs arrive simultaneously can they overcome the inhibition and elicit activity. And once activity is elicited, inhibition is important for keeping the excitation in check and resetting the circuit.

From Wikipedia: GABA acts by binding to specific receptors in the plasma membrane of both pre- and postsynaptic cells. This binding causes the opening of ion channels to allow either the flow of negatively-charged chloride ions into or positively-charged potassium ions out of the cell. This will typically result in a negative change in the transmembrane potential.

Three general classes of GABA receptor are known. These include GABA_A and GABA_C ionotropic receptors, which are ion channels themselves, and GABA_B metabotropic receptors, which are G protein-coupled receptors that open ion channels via intermediaries

From The Synaptic Self:Glutamate receptors (such as the NMDA receptor) tend to be located out on the dendrites, especially in the spines, whereas GABA receptors tend to be found on the cell body, or on the part of dendrites close to the cell body. In order for glutamate-mediated excitation to reach the cell body to help trigger an action potential, it has to get past the GABA guard. Excitation coming down a dendrite and headed for the cell body can be extinguished by GABA.

Without GABA inhibition, neurons would send out action potentials continuously under the influence of glutamate, and would eventually literally fire themselves to death. ... Overactivity of glutamate, and the resulting injury to neurons, actually plays an important role in stroke and other vascular disorders of the brain, as well as in epilepsy and possibly Alzheimer's disease.

This is Spinal Tap - Dendritic Spines

2008-06-13T23:09:00.000-07:00

The picture at right is truly amazing. It overlays three color-coded images of dendritic spines in a living mouse's brain, collected 45 minutes apart. White regions indicate stable dendritic segments. Green shows spines that retracted and red shows spines that sprouted during the observation period.

From A New Window to View How Experiences Rewire the Brain: Howard Hughes Medical Institute researchers have developed sophisticated microscopy techniques that permit them to watch how the brains of live mice are rewired as the mice learn to adapt to new experiences.

Their studies show that rewiring of the brain involves the formation and elimination of synapses, the connections between neurons. The technique offers a new way to examine how learning can spur changes in the organization of neuronal connections in the brain.
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“Our first observations of the large-scale structure of neurons, their axons and dendrites, revealed that they were remarkably stable over a month.” Dendrites and axons are highly branched structures, where dendrites are the input side of neurons and axons the output side.

“However, when we zoomed in closer, we found that some spines on dendrites appeared and disappeared from day to day,” said Svoboda. These spines stipple the surface of dendrites, like twigs from a branch, and form the receiving ends of synapses, which are the junctions between neurons where neurotransmitters are released.

“This finding was quite unexpected, because the traditional view of neural development has been that when animals mature, the formation of synapses ceases, which is indicated by stable synaptic densities,” said Svoboda. “However, the flaw in this view has been that a stable density only indicates a balanced rate of birth and death of synapses. It doesn’t imply the absence of the formation of new synapses, but it was often interpreted that way.”

In their experiments, Svoboda and his colleagues observed that about twenty percent of spines disappeared from one day to the next, offset by the formation of new spines.

“While we were surprised at the rate of turnover of some spines, we were also surprised at the incredible stability of other spines,” said Svoboda. The spines appeared to fall into different classes. And while there were those that turned over rapidly, other spines, typically the larger ones, persisted for months.

For this post, I've pulled together a lot of different articles on dendritic spines. They are amazingly complex, and are remarkably self-sufficient - they've got local mitochondria for powering their cellular machinery, can not only locally assemble proteins but also control the structure of the proteins that are to be assembled there, and can control their shape to help preserve long term memories...

From ScienceDaily (Dec. 22, 2004): Compared with most cells, neurons are more elongated and complex. Neurons are divided into different sections: the long, thin axon and the branching, tree-like dendrites that receive signals from other neurons via the suction cup-shaped synapses. Synapses, tiny gaps separating neurons, consist of a presynaptic ending at the very tip of an axon that contains neurotransmitters, a postsynaptic ending that contains neurotransmitter receptor sites, and the space between the two endings. Both presynaptic and postsynaptic endings require the energy generated by mitochondria.

Critical functions, such as synapses' transmission of information and ability to change rapidly in response to stimuli, are managed by distant cellular compartments that can become isolated from their nearest mitochondria. Sheng and postdoctoral fellow Zheng Li explored whether having the power source far away, like a too-distant room heater, would affect synaptic function.

The researchers looked at mitochrondria in living hippocampal neurons. The hippocampus, a seahorse-shaped brain region in the temporal lobe, is known to play a critical role in memory.

When synapses were stimulated, the researchers found, mitochrondria in the dendrites changed from being long and thin to more aggregated, collecting in globules near the enlarged dendritic spines, as if the mitochondria were reporting for duty at the active part of the neuron.

"Our studies reveal that mitochrondria dynamically redistribute into dendritic protrusions in response to synaptic excitation … The dendritic distribution of mitochondria appears to be an essential and limiting factor for synaptic density and plasticity," the authors wrote. If mitochondria don't migrate into the distant reaches of the dendrites--where most synapses are present--the synapses become less numerous and lose some of their ability to respond to external input. Enhancing mitochondria with the nutrient creatine also promoted synaptic density, the study showed.

ScienceDaily (Jan. 15, 2006): Harvard University biologists have identified a molecular pathway active in neurons that interacts with RNA to regulate the formation of long-term memory in fruit flies. The same pathway is also found at mammalian synapses.

Changes in the dendrites themselves outside of the synaptic region have also been shown to be critical to memory formation. From ScienceDaily (Nov. 3, 2005): Neurons experience large-scale changes across their dendrites during learning, say neuroscientists at The University of Texas at Austin in a new study that highlights the important role that these cell regions may play in the processes of learning and memory.
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Dendrites--the thin branch-like extensions of a neuron cell--receive many inputs from other neurons that transmit information through contact points called synapses. Much attention has been focused on the role that changes at synapses play in learning. They change in ways that make it easier for connected neurons to pass information.

Johnston and his colleagues show that learning and memory are likely to not only involve changes at synapses, but also in dendrites. They found that h-channels, which are distributed throughout the dendrite membrane and allow the passage of potassium and sodium ions into and out of the neuron, are altered during learning.

"The h-channels undergo plasticity, not near the synapse but probably throughout the dendritic tree," says Johnston.

To record the changes during learning, cells from the rat hippocampus (an important area of the brain for short-term memory) were electrically stimulated using a high frequency pattern called theta-bursts. Theta-bursts mimic the electrical stimulus that shoots through neurons when animals perform a learning task. The researchers found that when stimulated with theta-bursts, hippocampus neurons showed h-channel plasticity and a rapid increase in the synthesis of h-channel proteins.

The proteins were produced in the rat hippocampal neurons within 10 minutes, which is pretty rapid for cells, says Johnston.

"This really pushes the envelope with respect to how fast a neuron can produce new proteins important for learning," he says.

Learning and memory researchers know that protein synthesis in neurons is related to long-term memory, because protein synthesis inhibitors block long-term memory in animals.

Johnston says it's possible that the new proteins are being used by the neuron to build more h-channels in the dendrite membrane. He has a working hypothesis that h-channels may help buffer receiving neurons from being barraged and over-stimulated by inputs coming from information transmitting neurons.

From the article RNA splicing occurs in nerve cell dendrites: Researchers at the University of Pennsylvania School of Medicine have discovered that nerve-cell dendrites have the capacity to splice messenger RNA (pre-mRNA), a process once believed to only take place in the nucleus of cells.
In the nucleus of a mammalian cell, a gene is copied into mRNA, which possesses both exons (mature mRNA regions destined to code for proteins) and introns (non-coding regions). mRNA splicing works by cutting out introns and merging together the remaining exon pieces, resulting in an mRNA capable of being translated into a specific protein.

The vast array of proteins within the human body arises in part from the many ways that mRNAs can be spliced and reconnected. Specifically, splicing removes pieces of intron and exon regions from the RNA, with the resulting spliced RNA often being made into protein. Should the RNA have different exons spliced in and out of it, then different proteins can be made from this RNA.
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Dendrites, which branch from the cell body of the neuron, play a key role in the communication between cells of the nervous system, allowing for many neurons to connect with each other to form a network. Dendrites detect the electrical and chemical signals transmitted to the neuron by the axons of other neurons. The synapse is the neuronal structure where this chemical connection is formed, and investigators surmise that the synapse is where learning and memory occur.
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Protein diversity is a key aspect to the complexity of the central nervous system. Proteins are the workhorses of the cell and are generally responsible for insuring that cells function properly. When proteins interact with one another they can elicit specific physiological responses, including the generation and maintenance of memories. Changing protein identity, as can occur with splicing, can change the ability of the protein to interact with other proteins and therefore potentially change such physiological processes. With the dendrite being the initial site in the neuron where learning is thought to occur, the ability to create a diversity of mRNAs, through local splicing, and subsequent protein translation may permit exquisitely sensitive control of these cellular functions.

"The regulation and timing of the expression of proteins is what makes the central nervous system function," says Eberwine. The diversity and redundancy of the nervous-system proteins may serve to help maintain the system over a lifetime. However, failure in protein regulation or proper expression in neurons may give rise to cognitive dysfunction. "Most neurodegenerative and psychiatric illnesses exhibit dendrite dysfunction, therefore, the inability to properly generate spliced RNAs in dendrites or proteins may underlie aspects of these disease processes."

From ScienceDaily (Sep. 24, 2007): A molecular "recycling plant" permits nerve cells in the brain to carry out two seemingly contradictory functions -- changeable enough to record new experiences, yet permanent enough to maintain these memories over time. Michael Ehlers of Duke University Medical Center has done a study that shows the importance of receptor recycling in the dendritic spines plays in maintaining memories. "This process occurs on a time scale of minutes or hours, so the acquisition of new neurotransmitter receptors and their recycling is an on-going process. Memory loss may result from receptors escaping from the synapse. ... We believe that the existence of this recycling ability explains in part how individual dendritic spines retain their unique identity amidst this constant molecular turnover," Ehlers said. "The system is simultaneously dynamic and stable. ... If the receptors don't get recycled, you see a gradual loss of synaptic function that is associated with reduced cognitive ability," Ehlers said. "These dendritic spines are where learning and memories reside. These are the basic units of memory." (See the post on Clathrin - the super cool cellular transport machine for more information on receptor recycling.)

From Establishing Synaptic Independence: How Neurons Create Diffusional Barriers by Bernardo Sabatini: The optimal diffusional isolation of each spine likely depends on the state of the associated synapse. For example, at certain times the synapse may need to exchange components with the dendrite, requiring a relatively open neck. At other times, it may be beneficial to constrict the neck and favor the accumulation of plasticity-inducing molecules in the spine head. We found that the strength of diffusional coupling across the neck is a dynamically regulated parameter that is adjusted in response to changes in activity levels. Furthermore, the diffusional isolation of each synapse is controlled by a local signaling loop, such that when a synapse and the postsynaptic cell are consistently coactive, the neck of the spine that houses the active synapse is rapidly constricted. Since these patterns of activity are known to induce strengthening of hippocampal synapses, we propose that adjusting the properties of the neck may titrate the threshold for plasticity induction by determining the lifetimes of plasticity-inducing molecules near active synapses.

More...
Synapses in a State: A Molecular Mechanism to Encode Synaptic History and Future Synapse Function by Johanna Montgomery
Dynamin-dependent NMDAR endocytosis during LTD and its
dependence on synaptic state discusses the idea of synaptic state

Actin Lessons Part II: Memorabilia

2008-06-09T19:09:00.000-07:00

Recall from the previous post, that when a neuron's axon fires repeatedly the relevant genes (in that neuron) turn on, and the synapses that are holding the short-term memory when the synapse strengthening proteins find them, become, in effect, tattooed (from Making Memories Stick by R. Douglas Fields)

It appears that this 'tattooing' process involves enzymes that cause actin to change the shape of the synapse, broadening it so that more receptors can be brought into play. Much progress has been made in the past 10 years or so to understand the details of what is going on.

From ScienceDaily (Jun. 14, 2004): Neuroscientists at the Picower Center for Learning and Memory at MIT show for the first time that storage of long-term memories depends on the size and shape of synapses among neurons in the outer part of the brain, the cerebral cortex.
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When an experience or a fact is repeated enough or elicits a powerful emotional response, it shifts from short- to long-term memory. It moves from the hippocampus, in the innermost fold of the temporal lobe, to the brain’s outermost region, the cortex, which controls higher functions like abstract thought and speech. MIT researchers studied how structural and functional alterations of synapses--physical and chemical connections among neurons--in the cortex affect the animal’s ability to store long-term memory.

The MIT research provides the first evidence that synaptic structure and function in the cortex are critical for their long-term storage as memories are transferred from the hippocampus to the cortex.

PAK (p21-activated kinase), a critical regulator of synaptic architecture, was inhibited in the mutant mice. In humans, the gene that encodes this enzyme is tied to mental retardation. "Overall, we believe that one of the underlying mechanisms for mental retardation is synaptic malformation that leads to cognitive dysfunction," Hayashi said. "One of the most significant findings of this study is that the structure of synapses links to the function of synapses, and the size of synapses reflect the strength of the synapse. The bigger the synapse, the more vesicles to carry more neurotransmitters and the more channel proteins to permeate and bind to the neurotransmitters."

From Science Daily: University of California, Irvine researchers, using newly developing microscope techniques, have captured first-time images of the changes in brain cell connections following a common form of learning.

Detailed in the Journal of Neuroscience, the study shows that synaptic connections in a region of rats’ brains critical to learning change shape when the rodents learn to navigate a new, complex environment. In turn, when drugs are administered that block these changes, the rats don’t learn, confirming the essential role the shape change plays in the production of stable memory. “This is the first time anyone has seen the physical substrate, the ‘face,’ of newly encoded memory." said Gary Lynch, professor of psychiatry and human behavior at UC Irvine and leader of one of the two research teams involved in the studies.

The new behavioral experiments followed a series of recent discoveries by the UC Irvine group concerning the synaptic changes responsible for long-term potentiation (LTP), a physiological effect closely related to memory storage. Those studies used brain slices from rats, maintained alive in experimental chambers, to identify chemical markers for synapses that had recently experienced the LTP effect. The new study used live animals.

Working with advanced microscopic techniques called restorative deconvolution microscopy, the UC Irvine team found that the LTP-related markers appear during learning and are associated with expanded synapses in the hippocampus. Because the size of a synapse relates to its effectiveness in transmitting messages between neurons, the new results indicate that learning improves communication between particular groups of brain cells.

Because proteins continually biodegrade, ongoing maintenance operations need to be performed within the synapse or else it will not keep its shape. Prof. Yadin Dudai and his colleagues at the Neurobiology Department of Weizman Institute of Science have found that the process of storing long-term memories involves a miniature molecular machine that must run constantly to keep memories going. They also found that jamming the machine briefly can erase long-term memories. Their findings, which appeared today in the journal Science, may pave the way to future treatments for memory problems.

Dudai and research student Reut Shema, together with Todd Sacktor of the SUNY Downstate Medical Center, trained rats to avoid certain tastes. They then injected a drug to block a specific protein into the taste cortex – an area of the brain associated with taste memory. They hypothesized, on the basis of earlier research by Sacktor, that this protein, an enzyme called PKMzeta, acts as a miniature memory 'machine' that keeps memory up and running. An enzyme causes structural and functional changes in other proteins: PKMzeta, located in the synapses – the functional contact points between nerve cells – changes some facets of the structure of synaptic contacts. It must be persistently active, however, to maintain this change, which is brought about by learning. Silencing PKMzeta, reasoned the scientists, should reverse the change in the synapse. And this is exactly what happened: Regardless of the taste the rats were trained to avoid, they forget their learned aversion after a single application of the drug. The technique worked as successfully a month after the memories were formed (in terms of life span, more or less analogous to years in humans) and all signs so far indicate that the affected unpleasant memories of the taste had indeed disappeared. This is the first time that memories in the brain were shown to be capable of erasure so long after their formation.

'This drug is a molecular version of jamming the operation of the machine,' says Dudai. 'When the machine stops, the memories stop as well.' In other words, long-term memory is not a one-time inscription on the nerve network, but an ongoing process which the brain must continuously fuel and maintain. These findings raise the possibility of developing future, drug-based approaches for boosting and stabilizing memory.

Oster, Eichele and Leitges of The Max-Planck Institue provide more info on PKMzeta here. They've found that PKMzeta is found to be broadly expressed in most of the cortex, the limbic system, and the thalamus.

Another key protein is a-CaMKII. From ScienceDaily (May 21, 2001) A study by scientists from UCLA and Johns Hopkins University reveals the role of a protein that must be present in the cortex for information to be converted from short-term into lifelong memories. It indicates that the a-CaMKII protein triggers changes in cell-to-cell communication needed for establishing permanent memories in the cortex.

This was followed up by research from Yale - ScienceDaily (Mar. 16, 2005): A family of proteins that help build the cytoskeleton, or the bones of the cell, also play an important role in learning and memory, according to a study published in the Journal of Neuroscience 25: 2138–2145 (February–2005)

“If you learn to do something new, your neurons have to adapt and change to create a stronger, more direct pathway between neurons,” Picciotto said. “The protein ß–adducin appears to be important for making those new connections.”

In this study, the mice that did not have the protein were not able to strengthen a synapse in the hippocampus, which is the area of the brain that enables us to remember people, places and things. “If the mice don’t have ß–adducin, they can’t make a new map,” Picciotto said. “It’s not enough to just have the electrical properties, the (cyto)skeleton is very important in making long–lasting changes between nerve cells that result in learning.”

Nature has a review called "Actin in action: the interplay between the actin cytoskeleton and synaptic efficacy" by Cingolani and Goda that ties together many of these discoveries into a coherent picture: Synapse regulation exploits the capacity of actin to function as a stable structural component or as a dynamic filament. Beyond its well-appreciated role in eliciting visible morphological changes at the synapse, the emerging picture points to an active contribution of actin to the modulation of the efficacy of pre- and postsynaptic terminals. Moreover, by engaging distinct pools of actin and divergent signalling pathways, actin-dependent morphological plasticity could be uncoupled from modulation of synaptic strength.

From the corrected version of Box 3 of the article: Synaptic activity regulates actin dynamics and spine morphology through multiple signalling pathways. Key regulators of actin polymerization are the GTPases of the Rho family and serine/threonine kinases, which ultimately target actin-binding proteins (Table 1).

In the figure, actin-binding proteins are shown in red, Rho GTPases are shown in blue, kinases are shown in golden yellow, phosphatases are shown in green and GEFs are shown in dark orange.

In dendritic spines, opening of the Ca2+-permeable NMDA (N-methyl-D-aspartate) receptors by repetitive synaptic stimulation leads to the elevation of intracellular Ca2+ and the subsequent activation and translocation of Ca2+/calmodulin-dependent protein kinase II (CaMKII) to the postsynaptic density. Once activated, CaMKII can phosphorylate and activate multiple downstream signalling targets.

In addition, CaMKII, which is present in dendritic spines at high levels, has been proposed to also function as a structural molecule that can bind to and bundle F-actin through its subunit. Among the intracellular signalling events that are relevant for actin dynamics, of particular interest is the activation of the calmodulin-dependent kinase kinase (CaMKK)–CaMKI signalling pathway. These kinases form a multimolecular complex with the guanine-nucleotide exchange factor (GEF) PIX.

CaMKI-mediated phosphorylation of PIX increases its GEF activity, resulting in the activation of the small GTPase Rac1. PIX also interacts with p21-activated kinase 1 (Pak1), which can be activated by Rac1-triggered autophosphorylation.

In turn, Pak1 phosphorylates several downstream signalling molecules that directly modulate F-actin. For instance, Pak1-mediated phosphorylation activates LIM kinase (LIMK). The only known targets of LIMK are the members of the ADF/cofilin family (actin-depolymerizing proteins), which are inactivated upon LIMK-mediated phosphorylation.

Alternatively, Rac1 can be activated by a second GEF, kalirin 7, which interacts with and is phosphorylated by CaMKII. The activation of LIMK can also be promoted by the small GTPase RhoA, through RhoA-specific kinase (ROCK).

Interestingly, RhoA interacts with NMDA receptors, ROCK and the actin-polymerizing protein profilin II in an activity-dependent manner. Also,alpha-actinin, which is involved in crosslinking and bundling actin filaments, associates with NMDA receptors in an activity-dependent manner. When NMDA receptors open in response to stimuli delivered at low frequency to induce long-term depression, the effects on actin dynamics are opposite to those of CaMKII-initiated pathways, as ADF/cofilin family proteins are turned on following the activation of the phosphatase calcineurin.

More...
ScienceDaily (Nov. 10, 2000): info on NMDA receptors

Will you remember me? I will remember you...

2008-05-22T20:47:00.000-07:00

If there was one experience that pushed my interest in neurobiology beyond the activation threshold and kick-started the process that led to the creation of this blog, it was reading Dr. R. Douglas Fields' article "Making Memories Stick" in the Feb. 2005 issue of Scientific American (ref.). I'd long been interested in molecular biology but had been intimidated by the level of jargon and assumed knowledge that filled most articles. Dr. Fields' article explained the inner workings of a neuron so clearly and lucidly that I was able to get a basic understanding of what was happening, and was motivated to try to learn more about molecular biology and neurobiology in particular. This blog is essentially the notes I've been making as I try to learn more about the details of how biology works at a molecular, cellular and neuronal level. So, things have finally come full circle. Let's take a deeper look at what makes memories stick...

From Making Memories Stick by R. Douglas Fields:
As far back as 1949, a psychologist named Donald Hebb ...proposed that, like an orchestra player who cannot keep up, a synapse on a neuron that fires out of sync with the other inputs to the neuron will stand out as odd and should be eliminated, but synapses that fire together - enough so as to make the nueron fire an action potential - should be strengthened. The brain would thus wire itself up in accordance with the flow of impulses through developing neural circuits, refining the original general outline.
...
By stimulating neurons to fire action potentials in different patterns and then measuring the amount of mRNA from genes known to be important in forming neural circuits or in adapting to the environment, we found ...we could turn on or off particular genes simply by dialing up the correct stimulus frequency on our electrophysiological stimulator, just as one tunes into a particular radio station by selecting the correct signal frequency.
...
If [the hippocampus] is dissected from a rat and kept alive in a salt solution, microelectrodes and electronic amplifiers can record the electrical impulses from individual synaptic connections on a neuron. By administering a burst of electrical shocks to a synapse, causing it to fire in a specific pattern, that synaptic connection can be strengthened. That is to say, the synapse produces about twice as much voltage in response to subsequent stimulations after it has received the high-frequency stimulus.
This increased strength, termed long-term potentiation (LTP), can be, despite its name, relatively short-lived. When test pulses are applied at a series of intervals after the high frequency stimulus, the voltage produced by the synapse slowly diminishes back to its original strength within a few hours. Known as early LTP, this temporary synaptic strengthening is a cellualr model of short-term memory.

Remarkably, if the same high-frequency stimulus is applied repeatedly (three times in our experiments), the synapse becomes strengthened permanently, a state called late LTP. But the stimuli cannot be repeated one after the other. Instead, each stimulus burst must be spaced by sufficient intervals of inactivity (10 minutes in our experiments). And adding chemicals that block mRNA or protein sysnthesis to the salt solution bathing the brain slice will cause the synapse to weaken to its original strength within two to three hours. Just as in whole organisms, the cellular model of short-term memory is not dependent on the nucleus, but the long-term formation of memory is.
...
Strong stimulation, either from the repeated firing of a single synapse or from the simultaneous firing of several synpases on a cell, depolarizes the cell membrane, causing the cell to fire action potentials of its own, which in turn causes voltage-sensitive calcium channels to open. The calcium ions interact with enzymes that activate the transcription factor CREB, which activates the genes for manufacturing synapse-strengthening proteins. The cell's nucleus "listens," in effect, to the cell's output - firing action potientials - to determine when to permanently strengthen a synapse and make a memory last. (see diagram at top of post.
More info on the role CREB plays is available here.)
...
One does not always know beforehand what events should be commmited permanently to memory. The moment-to-moment memories necessary for operating in the present are handled well by transient adjustments in the strength of individual synapses. But when an event is important enough or is repeated enough, synapses fire to make the neuron in turn fire neural impulses repeatedly and strongly, declaring "this is an event that should be recorded". The relevant genes turn on, and the synapses that are holding the short-term memory when the synapse strengthening proteins find them, become, in effect, tattooed.

(Some recent research that explains how this 'tattooing' works will be covered in the next post). From another excellent article by Dr. Fields, Erasing Memories (SciAm Mind Dec 2005):
There is a complication, however. The molecules that establish current flow around synapses are proteins, and all proteins in the body degrade and are replaced constantly over a period of hours or days. To strengthen a neural connection for a lifetime, some other process must take place to bolster the physical structure of a synapse or form additional synapses between the neurons involved.
The transition from temporary to permanent memory is called consolidation. Many experiments have deterined that consolidation requires many hours, and it can be enhanced or blocked in various ways. ... If the next 10 seconds of your life could be your last, you will remember them, even if the interval is folowed by another 10 dramatic seconds, and so on. ... The heightened state of attention, stress and novelty stimulates the consolidation phase of memory.
Neuroscientists have discovered how this consolidation happens. An epinephrine (a.k.a. adrenaline) rush releases a flood of stress hormones and neurotransmitters that activate the amygdala, the brain region that processes fear and emotion. The amygdala connects to many other regions where different kinds of memories are stored, and it boosts incoming data that have emotional impact. Consolidation, therefore, possibly can be aided by increasing levels of these neurotransmitters or hormones.
...
A growing body of evidence suggests that memory consolidation continues "off-line" while we sleep, in part because sleep involves periodic surges of some of the same hormones and neurotransmitters that are aroused in stressful and novel situations.

A research group headed by Jan Born at the University of Lübeck has found that sleep not only strengthens the content of a memory, but also the temporal structure of episodic memories, probably by replaying them in the forward direction (ScienceDaily (Apr. 18, 2007))

Returning to Erasing Memories:... [Work by Phillipe Peigneux] illustrates that memory consolidation requires sorting through fresh memories, integrating them with other memories, and shuttling them to different brain regions for permanent storage. Short-term memories deemed dispensible are discarded.
...
[James R. Misanin and others at Rutgers University] found that a consolidated memory could be erased if a lab rat was shocked right after being forced to recall the experience. ... [R]ecalling the memory had somehow made it vulnerable to disruption. This phenomenon has been termed reconsolidation.

In the article, Dr. Fields mentions that research by Joseph E. LeDoux and his colleagues at New York University has shown that microinjecting protein synthesis inhibitors into a rat's amygdala can block memory reconsolidation if applied shortly after the memory is recalled.
From Joseph LeDoux's book The Synaptic Self: The recent discovery , made by Karim Nader and Glenn Schafe in my lab, is that protein synthesis in the amygdala seems necessary for a recently activated memory to be kept as a memory. That is, if you take a memory out of storage you have to make new proteins (you have to restore, or reconsolidate it) in order for the memory to remain a memory. One way of thinking about this is that the brain that does the remembering is not the brain that formed the initial memory. In order for the old memory to make sense in the current brain, the memory has to be updated.

From Cellular and Systems Reconsolidation in the Hippocampus by Jacek Debiec, Joseph E. LeDoux and Karim Nader:
Indeed, reconsolidation and consolidation have been found to share a number of common properties, including: (1) requirement of protein synthesis in order for the memory to persist, (2) time windows during which protein synthesis blockade is effective, and (3) that protein synthesis blockage in the same brain region, the amygdala, disrupts both. Given these similarities, it seemed parsimonious to conclude that a new memory and a reactivated, consolidated memory share a common memory state, as originally proposed by Lewis (1979). Thus, instead of just occurring once, memory storage may instead be a process that is reiterated with each use of the memory.

... and from the abstract:
Cellular theories of memory consolidation posit that new memories require new protein synthesis in order to be stored. Systems consolidation theories posit that the hippocampus has a time-limited role in memory storage, after which the memory is independent of the hippocampus. Here, we show that intra-hippocampal infusions of the protein synthesis inhibitor anisomycin caused amnesia for a consolidated hippocampal-dependent contextual fear memory, but only if the memory was reactivated prior to infusion. The effect occurred even if reactivation was delayed for 45 days after training, a time when contextual memory is independent of the hippocampus. Indeed, reactivation of a hippocampus-independent memory caused the trace to again become hippocampus dependent, but only for 2 days rather than for weeks. Thus, hippocampal memories can undergo reconsolidation at both the cellular and systems levels.

Do you remember this quote, near the start of Dr. Fields' article 'Making Memories Stick': Donald Hebb ...proposed that, like an orchestra player who cannot keep up, a synapse on a neuron that fires out of sync with the other inputs to the neuron will stand out as odd and should be eliminated.?
The official term for the weakening of unhelpful synapses such as these is Long Term Depression (LTD). From the Howard Hughes Medical Institute (2004) LTP and LTD: strengthening and weakening synaptic connections

OUT OF SYNC, LOSE THE LINK
"The prevailing view used to be 'use it or lose it,'" says Bear. But a more accurate conclusion may be "neurons that fire out of sync lose their link.
...
When a neuron receives mismatched signals, synapses lose receptors ... If the loss of receptors is sufficiently prolonged, Bear suspects, the synapse eventually will disappear.
...
Bear's research into LTD has had other, and sometimes quite unexpected, consequences. His lab also has investigated a form of LTD triggered by the activation of another receptor on receiving neurons. One of the proteins affected by this receptor is the one that's missing in fragile X syndrome, the most common cause of inherited mental retardation in humans.

As always, the more I learn about things the more questions I have! Next post, we'll zoom in further to look at the changes the synapse undergoes when it is 'strengthened', and then start to zoom out to look at memory from a higher 'system-level' perspective.

More...
Podcast interview with R. Douglas Fields
Synapse signalling complexes and networks: machines underlying cognition" by Seth G.N. Grant

Actin Lessons - part 1. Cytoskeletal proteins are similar to G-proteins

2008-01-23T17:35:00.000-08:00

I happened to stumble upon Martin Rodbell's 1994 Nobel Lecture paper: "Signal Transduction: Evolution of an Idea" again recently. I really enjoy reading these Lecture papers as they are a) written by the scientists that did the breakthrough research, b) contain a lot of insights into the creative process behind their discoveries and c) are intended for a general audience. Rodbell's paper is a good example. The following excerpt from his lecture paper bridges two areas I had no idea were related: G-protein receptors and the cytoskeleton. (The picture at right is from the web page for Andres Lebensohn of the Kirschner Lab at Harvard. It shows the assembly of an actin network.)

G-PROTEINS ARE SIMILAR IN STRUCTURE AND REGULATION TO
CYTOSKELETAL PROTEINS. by Martin Rodbell

During these studies, my attention was drawn to the striking similarities in the properties of G-proteins with those of tubulin and actin, the major cytoskeletal elements in cells. For example, G-proteins, like actin and tubulin, are associated with the inner aspect of the surface membrane, adhering possibly both through intrinsic membrane proteins, such as receptors, and to membrane lipids. Of particular interest is the fact that all three types of multimeric proteins are subject to regulation by either GTP (G-proteins and tubulin) or ATP (actin) and their hydrolytic products (dinucleotides and Pi). Receptors regulate exchange of bound nucleotides (GDP with GTP) and act catalytically in the process. Similarly, the excursion of a single myosin molecule during muscle contraction along the chain of actin multimers is governed by the exchange of bound ADP with ATP and the hydrolysis of ATP to ADP and Pi. As stated previously, GTP-turnover (production of GDP+Pi) is essential for the rapid and sustained actions of hormones; release of bound Pi is the crucial rate-limiting process in the overall dynamics of signaling. The same is true for myosin/ actin interactions.

With these similarities in structure and regulation, G-proteins can be classified as part of the cytoskeletal matrix, with the primary functional difference that G-proteins serve as chemical signaling devices whereas tubulin and actin serve as mechano-signaling devices. The release of monomers from multimers is the basis for chemical signaling by G-proteins. Dynamic changes in the disaggregation-aggregation cycle of actin and tubulin multimers are also regulatory devices designed for regulating the interactions or movement between specialized components of cells. Based on evidence accumulated over the past decade, all three types of cytoskeletal proteins are connected in some manner to a variety of signaling systems that adhere to the cytoskeletal matrix, including heterotrimeric G-proteins, so-called small molecular weight G-proteins, protein kinases and phosphatases, and other proteins or systems that communicate between the surface membrane and the interior of cells. These components form web-like structures that possibly interact in a flickering manner in response to activation of membrane receptors, including those that are growth promoting.

This is particularly fascinating given the recent breakthroughs in understanding the functional basis of memory formation that point to a physical change in the shape of the synapse (i.e. a cytoskeletal response to a neural action potential) as well as some of the molecular machinery that keeps the synapse in this configuration. My next blog will dig into what is currently known about how memories are formed in more depth.

Station to Station: Action Potentials in Neurons

2007-09-09T04:56:00.000-07:00

Overview

From Sandra Ackerman's book Discovering the Brain: The actual signals transmitted throughout the brain come in two forms, electrical and chemical. The two forms are interdependent and meet at the synapse, where chemical substances can alter the electrical conditions within and outside the cell membrane.

A nerve cell at rest holds a slight negative charge (about –70 millivolts, or thousandths of a volt, mV) with respect to the exterior; the cell membrane is said to be polarized. The negative charge, the resting potential of the membrane, arises from a very slight excess of negatively charged molecules inside the cell.

A membrane at rest is more or less impermeable to positively charged sodium ions (Na⁺), but when stimulated it is transiently open to their passage. The Na⁺ ions thus flow in, attracted by the negative charge inside, and the membrane temporarily reverses its polarity, with a higher positive charge inside than out. This stage lasts less than a millisecond, and then the sodium channels close again. Potassium channels (K⁺) open, and K⁺ ions move out through the membrane, reversing the flow of positively charged ions. (Both these channels are known as voltage-gated, meaning that they open or close in response to changes in electrical charge occurring across the membrane.)

Over the next 3 milliseconds, the membrane becomes slightly hyperpolarized, with a charge of about –80 mV, and then returns to its resting potential. During this time the sodium channels remain closed; the membrane is in a refractory phase.

An action potential—the very brief pulse of positive membrane voltage—is transmitted forward along the axon; it is prevented from propagating backward as long as the sodium channels remain closed. After the membrane has returned to its resting potential, however, a new impulse may arrive to evoke an action potential, and the cycle can begin again.

Gated channels, and the concomitant movement of ions in and out of the cell membrane, are widespread throughout the nervous system, with sodium, potassium, and chlorine being the most common ions involved. Calcium channels are also important, particularly at the presynaptic boutons of axons. When the membrane is at its resting potential, positively charged calcium ions (Ca²⁺) outside the cell far outnumber those inside. With the advent of an action potential, however, calcium ions rush into the cell. The influx of calcium ions leads to the release of neurotransmitter into the synaptic cleft; this passes the signal to a neighboring nerve cell.

Having taken a close look at the electrical side of the picture, we are in a better position to see where the chemistry comes in. Molecules of neurotransmitter are released into a synaptic cleft and bind to specific receptor sites on the postsynaptic side (the dendrite or dendritic spine), thereby altering the ion channels in the postsynaptic membrane. Some neurotransmitters cause sodium channels to open, allowing the influx of Na⁺ ions and thus a lessening of negative charge inside the cell membrane. If a considerable number of these potentials are received within a short interval, they can depolarize the membrane enough to trigger an action potential; the result is the transmission of a nerve impulse. The substances that can cause this to occur are the excitatory neurotransmitters. By contrast, other chemical compounds cause potassium channels to open, increasing the outflow of K⁺ ions from the cell and making excitation less likely; the neurotransmitters that bring about this state are considered inhibitory.

A given neuron has a great quantity of sites available on its dendrites and cell body and receives signals from many synapses simultaneously, both excitatory and inhibitory. These signals often amount to a rough balance; it is only when the net potential of the membrane in one region shifts significantly up or down from the resting level that a particular neurotransmitter can be said to be exerting an effect. Interestingly, in the membrane's overall balance sheet, the importance of a particular synapse varies with its proximity to where the axon leaves the nerve cell body, so that numerous excitatory potentials out at the ends of the dendrites may be overruled by several inhibitory potentials closer to the soma. Other kinds of synapse regulate the release of neurotransmitters into the synaptic cleft, where they go on to affect the postsynaptic channels as described above.

So, let's dig into this in more detail:

In every living cell there is always a difference in electrostatic potential between the inside and outside of a cell: the cell is polarized. (ref 1,ref 2). This membrane potential is due to ion pumps such as Na-K-ATP-ase, an enzyme. Within cells, the concentration of Na+ ions is lower, and that of K+ ions higher, than in the surrounding fluid. Na+, K+-ATPase and other ion pumps must work all the time in our body. If they were to stop, our cells would swell up, and might even burst, and we would rapidly lose consciousness. A great deal of energy is needed to drive ion pumps - in humans, about 1/3 of the ATP that the body produces.

The Na+, K+-ATPase enzyme exposes binding sites to 3 Na+ ions when opened to the inside of the cell, and binding sites to 2 K+ ions when opened to the outside of the cell, and uses the energy from ATP to change its shape from one configuration to the other. This results in a higher concentration of +ve ions outside of the cell than inside, as 3 Na+ ions are pumped out of the cell for every 2 K+ ions that are pumped into the cell. The resulting relative electric potential (voltage difference) is the driving 'electro motif force' (EMF) that causes ions to flow when ion channels, triggered by neurotransmitters, open.

From Fred Wolf's page at the Max Planck Institute for Dynamics and Self-Organization: Every living cell maintains a voltage difference across its cell membrane. (how this is done). Nerve cells distinguish themselves from other cells in that they use this voltage difference to process and transmit messages. When a nerve cell receives an impulse, the voltage across the cell membrane is reversed. This "action potential" spreads out through the long appendages of the cell with high speed. At the end of the appendages it is transmitted to other cells. In 1952, Alan Lloyd Hodgkin and Andrew Fielding Huxley described in a mathematical model how such an action potential originates on the basis of measurements on neurons of the squid. The Hodgkin-Huxley model, for which the scientists received the 1963 Nobel Prize in Medicine, has since then served to explain the signal processes in all neurons.

According to the Hodgkin-Huxley model, an action potential is initiated when the voltage across the membrane of the nerve cell reaches to a certain threshold value. Voltage gated sodium channels react to this voltage change by opening up and triggering an avalanche-like reaction. Positively charged sodium ions flow through the open channels into the cell, which leads to a further increase of the membrane potential and the opening of additional sodium channels. The threshold and the speed with which the action potential originates vary from cell to cell - for any individual cell however, these parameters are specified for the most part by the characteristics of its sodium channels.

There is always a difference in electrostatic potential between the inside and outside of a cell: the cell is polarized. the result of the distribution of ions across the cell membrane and the permeability of the membrane to these ions. The ion channels themselves are positioned and held in place by the cytoskeleton of the neuron. In fact the Baz/Par-6/aPKC complex, a highly conserved protein cassette that functions during the establishment of polarity in a number of cell types, is also involved in the development of new synaptic boutons. (ref.)

From the University of Bristol: How do neurons work? : Under resting conditions, the potassium channel is more permeable to potassium ions than the sodium channel is to sodium ions. So there is a slow outward leak of potassium ions that is larger than the inward leak of sodium ions. This means that the membrane has a charge on the inside face that is negative relative to the outside, as more positively charged ions flow out of the neuron than flow in. The membrane is said to be polarised.

From reference.com: The voltage of an inactive cell remains close to a resting potential with excess negative charge inside the cell. When the membrane of an excitable cell becomes depolarized beyond a threshold, the cell undergoes an action potential (it "fires), often called a "spike" (see Threshold and initiation).

An action potential is a rapid change of the polarity of the voltage from negative to positive and then vice versa, the entire cycle lasting on the order of milliseconds. Each cycle — and therefore each action potential — has a rising phase, a falling phase, and finally an undershoot (see Phases).

From http://www.du.edu/~kinnamon/3640/actionpotential/ap1.html : Conformational changes in the voltage-dependent Na⁺ channel constitute the basis of the action potential. Time course of an action potential: The opening of a few Na⁺ channels leads to an initial depolarization. If this depolarization exceeds a threshold value then a rapid regenerative opening of many other Na⁺ channels follows, resulting in the depolarizing phase of an action potential. Since the Na⁺ channel spontaneously inactivates, the repolarization of the membrane occurs automatically. (Reichert, Introduction to Neurobiology)

From the commentary by Frank Werblin, UC Berkely to his animated and interactive tutorial's action potential animation at http://mcb.berkeley.edu/courses/mcb64/action_potential.html :

The action potential begins with a small depoloarization that comes from somewhere else. This causes ALL ion gates involved to begin their openning trajectory, but each at a different rate. First the sodium activation gate at the top of the sodium channel begins to open, allowing the sodium to enter the membrane and depolarize it further. Then the sodium inactivation gate at the bottom of the sodium channel closes, terminating the inward flow of sodium.

More slowly, the potassium activation gate begins to open. There's an outward flow of potassium ions, hyperpolarizing the membrane. This outward flow continues until the membrane overshoots the resting level in the hyperpolarizing direction. The potassium gate opens with depolarization, but the current hyperpolarization causes the potassium gate to close, terminating the action potential. http://www.du.edu/~kinnamon/3640/actionpotential/ap1.html

Bucket Brigade

(The diagrams at right are from B. Fleming, U. of Waterloo )

From the University of Bristol: How do neurons work? :

Excess ions are subsequently pumped in/out of the neuron.

In some neurons, after hyperpolarization a secondary, longer-term effect occurs: a post-excitatory restoration of membrane potential, termed after-hyperpolarization (AHP).

If this were all there was to it, then the action potential would propagate in all directions along an axon. But action potentials move in one direction. This is achieved because the sodium channels have a refactory period following activation, during which they cannot open again. This ensures that the action potential is proagated in a specific direction along the axon.

For a neuron to integrate all of the various pulses that it is recieving from various other neurons, the pulses need to 'line up' to a certain degree in order to be 'coincident' and push the neuron over the activation threshold. For this to happen, the pulse width would need to be greater than the propagation delay introduced by the axon. The pulse width is on the order of 2ms. The propagation along an unmyelinated axon depends on a number of factors (e.g. the cross-sectional width of the axon, the type of axon, etc.) but is typically around 50 m/s. (ref.) which would imply that the axon needs to be less than 10 cm in length.

Axons that are used a lot become sheathed in 1 mm long sections of myelin (oligodendrocytes) that promote more efficient and faster conduction. The action potential in myelinated axons jumps from one gap in the myelin (called a 'node of Ranvier') to the next in a process called 'saltatory conduction'. Myelination causes the resistance of the membrane to increase by a factor of 200 and the capacitance per unit area of the axon to decrease by a factor of 200 (ref.)

Recent research by B. Stevens, S. Porta, L. Haak, V. Gallo and R. Douglas Fields has shown that axons release Adenosine in response to action potential firing and that this is used as a chemical signal by oligodendrocyte progenitor cells to initiate sheathing axons that fire frequently.

More information:

MASS ACTION IN THE NERVOUS SYSTEM EXAMINATION OF THE NEUROPHYSIOLOGICAL BASIS OF ADAPTIVE BEHAVIOR THROUGH THE EEG (2004) by Professor Walter J. Freeman University of California, Berkeley, USA (http://sulcus.berkeley.edu/MANSWWW/MANSHTML/MANSChapt3.html) : provides a lot of the equations and details about how neurons operate.

The sea inside your skull - ion homeostasis

2007-07-16T08:23:00.000-07:00

Previous posts have covered a number of the low-level building blocks that are used by cells in the brain - things like ion channels, neurotransmitters, receptors, clathrin, vesicles, etc. This post focuses on some important pieces of infrastructure that are needed to enable the brain to do its thing.

Neurons operate in an aqueous medium - a kind of salt water bath, water that is full of postively charged ions (cations like sodium, potassium and calcium) and negatively charged ions (anions like chlorine). Water molecules are V shaped and have a non-uniform distribution of charge - i.e. one end of the water molecule is more positively charged than the other end. Like charges repel and unlike charges attract. As a result, a sphere of these 'polar' water molecules tends to surround the ions (a 'sphere of hydration'). Complicating the picture further is the fact that charged particles like ions are influenced by both concentration gradients (ions flow to the region with the lower concentration of that ion) and electrical gradients (electro-magnetic fields, charge distribution)

The resting nerve has mostly Na+ on the outside of the membrane and K+ and negatively charged, non-diffusible protein on the inside. Because there is a little leakage of K+ to the outside (K+ is more permeable than Na+), the net membrane charge is positive on the outside and negative on the inside. (Ref.: PLASMA MEMBRANE AND MEMBRANE POTENTIAL IN THE NERVE CELL - U. of Colorado)

At rest, in the absence of action potentials or any other activity, the inside of a neuron has a voltage of about -65mV compared to the outside. Neural signals are changes in this resting potential. (Ref.: Neuronal Membrane at Rest: Ionic Basis of the Membrane Resting Potential)

The resting potential results from the establishment of ionic gradients across the cell membrane for potassium, sodium, chloride, and calcium. Most membranes are permeable principally to potassium and sodium. The diffusion pressure for each ion is balanced by an electrical force from the voltage that develops across the membrane. The voltage that exactly balances each ion is the equilibrium potential for that ion. The resting potential is a weighted average of the equilibrium potentials for the ions to which the membrane is permeable. The net driving force on a given ion is the difference between the membrane potential and its equilibrium potential. (ref.)

The above references get into the key equations that govern ionic behaviour: the Nernst Equation calculates the numerical value of the equilibrium potential, and the Goldman Equation calculates the membrane potential as a weighted average of the equilibrium potentials. Not going into these here :)

From the above, you can see that membranes are REALLY important. You need a membrane to separate two different environments with different characteristics in order to do any 'work'. Stuart Kauffman has some very interesting perspectives on this - I've added a new NanoBiologyNotes blog entry on Membranes that touches on these ideas.

Most neurons are interconnected indirectly with each other. An electrical 'action potential' flows down a neuron's axon until it reaches a terminating 'bouton' - a bulb containing mitochondria and tiny bubbles called vesicles that are filled with one or more kinds of neurotransmitters. The action potential causes the vesicles to fuse with the axon's membrane and releaseits payload of neurotransmitters into the synaptic gap that seperates it from another neuron's dendrites or soma. (We'll call this second neuron the 'receiving neuron'). These neurotransmitters bond with ion channels in the membrane of the receiving neuron, causing a conformational change in the shape of each of the ion channels which allows ions that are present in the fluid surrounding the neurons to flow into the receiving neuron, or ions that are inside of the neuron to flow out, depending on the type of ion channel that has been opened. A single neuron can have tens of thousands of these types of indirect connections with other neurons. If enough sending neurons trigger at rougly the same time, a large enough number of ion channels in the receiving neuron will be open that the ionic concentration of the receiving neuron will hit a threshold that initiates one or more action potentials to rush through the receiving neuron to it's axon. Roughly speaking.

But, uh, where do all of these ions come from? What establishes and maintains the correct concentration of ions outside of the neurons??

This simple question led me into some fascinating stuff on morphobiology, ph and H+ gradients, genetic toolkits and so much interesting material I'm starting up another blog to focus on it. But, back to the original question...what's up with the ions?

Zhi-Qi Xiong and Janet L. Stringfer (Baylor College of Medicine) published a nice introduction to what is going on to establish the right environment in the brain for neurons to work in the Journal of Neurophsiology (ref.) (I've removed the references from the text to improve readability - please see the original for these):

Neuronal activity is associated with a rise in the extracellular potassium concentration ([K⁺]_o) caused by efflux of potassium during action potential repolarization.Neuronal activity, in the absence of clearance mechanisms, wouldcause the [K⁺]_o to rise in seconds to values that would abolish all electricalactivity. However, it is known that during intenseevoked neuronal activity or spontaneous epileptiform activityin the cortex and hippocampus [K⁺]_o rises to a ceiling level of 10-12 mM from a resting level of3 mM. The occurrence of a plateau, or ceiling, level during continuedneuronal activity suggests that [K⁺]_o is actively cleared from the extracellularspace.

Clearing of excess [K⁺]_o is believed to occur by diffusion, active uptake by neurons and glia, or passive uptake by glia. There is evidence that the rate of potassium release duringrepetitive neuronal activity is faster than the rate at whichit would diffuse away. Although neurons can takeup potassium, uptake by astrocytes is believed to play a majorrole in regulation of [K⁺]_o. Glia are thought to be required for the normal fine tuningof [K⁺]_o and for the recovery of pathologically elevated [K⁺]_o. Glia have been shownto increase their internal potassium concentration when [K⁺]_o is increased and release it once the [K⁺]_o decreases. They are alsobelieved to remove potassium by spatial buffering through theglial syncytium. According to the spatialbuffering hypothesis, potassium released from active neurons enters glial cells,possibly through inwardly rectifying potassium channels. Potassiumis then redistributed through the network of glial cells and leavesat sites of low [K⁺]_o. Spatial buffering can be directly demonstrated in the droneretina as a result of a fortunate spatial arrangement of neuronaland glial structures. However, the exact role of glial spatial bufferingin other parts of the brain and during times when the regulationsystems are significantly stressed (i.e., during synchronous epileptiformactivity) is not clear. It has been argued that spatial bufferinghas no role in situations of elevated [K⁺]_o.

There's a nicely written article (Astrocytes) by Pierre J. Magistretti and Bruce R. Ransom that provides a good overview of the role played by glial cells:

The astrocyte is a ubiquitous type of glial cell that is defined in part by what it lacks: axons, action potentials, and synaptic potentials. Astrocytes greatly outnumber neurons, often 10:1 and occupy 25% to 50% of brain volume (1–3). Although these cells are anatomically obvious, their functions have been difficult to determine. Discoveries in the last 25 years, however, have revealed some of their functions and established the essential nature of interactions between neurons and astrocytes for normal brain function.
One of the best-established functions of astrocytes is regulation of brain [K]o. Astrocytes are also likely to participate in the regulation of extracellular pH.
Neural activity can rapidly increase [K]o, which is tightly regulated to a resting level of about 3 mM (25). A single action potential increases the instantaneous [K]o by0.75mM(26). The increase in [K]o is proportional to the intensity of neural activity but has a so-called ‘‘ceiling’’ level of accumulation of 10 to 12 mM (27,28), which is only exceeded under pathologic conditions (29). If diffusion alone were responsible for dissipating K released from neurons, it is easily calculated that extracellular K accumulation would exceed 10 mM during normal neural activity, whereas measured increases in [K]o are in the range of 1 to 3mMindicating powerful control mechanisms (30). Homeostatic control of [K]o is needed because brain [K]o can influence transmitter release (31), cerebral blood flow (32), ECS volume (33,34), glucose metabolism (35), and neuronal activity (36). Unchecked increases in [K]o act as an unstable positive feedback loop increasing excitability.
Astrocytes expedite the removal of evoked increases in [K]o and limit its accumulation to a maximum level of 10 to 12mM, the ceiling level seen with intense activity such as epileptic discharge (37,38). Neurons, and perhaps blood vessels, also participate in [K]o regulation, but glial mechanisms are probably most important. Two general mechanisms of astrocyte K removal have been proposed
(39): 1) net K uptake into astrocytes (by transport mechanisms and/or Donnan forces) and 2) K redistribution through astrocytes, which is known as K spatial buffering. The relative importance of these two mechanisms of [K]o regulation remains an open question and may depend on the nature of the [K]o increase as well as brain region (38). If glial cells take up K during neural activity and release it thereafter, a transient increase in glial [K]i should result. Astrocyte [K]i does transiently increase during neural activity and has a similar time course to the K lost from active neurons and the increase in [K]o, indicating that the K released from neurons is passing by way of the ECS into glial cells (40–42). Uptake of K into glial cells depends on the glial Na pump (38,42–44), an anion transporter that cotransports K and Na with Cl (43) and Donnan forces that propel KCl into glial cells in the face of elevated [K]o (42) (Fig 10.1). It has not been determined with certainty which of these mechanisms is quantitatively most important for K uptake. The astrocyte Na pump, however, is exquisitely sensitive to elevations of [K]o. Even a 1 mM increase in [K]o activates the Na pump in these cells indicating, perhaps, that this is the major mechanism of K sequestration (44). Neurons, of course, must eventually reaccumulate K lost during activity using their Na pump, but only glial cells show net accumulation
of K (Fig. 10.1). It is interesting to note that the neuronal Na pump is not sensitive to small increases in [K]o and is probably activated mainly by increases in intracellular [Na] (45).

Another key mechanism that plays an important role in regulating the ionic concentrations is something called the "Na⁺-K⁺-Cl^- cotransporter" (ref.)

Little is known regarding how Na⁺-K⁺-Cl^- cotransporter activity is regulated in the CNS. Glutamate, N-methyl-d-aspartate, and the metabotropic glutamate receptor agonist t-ACPD significantly stimulate cotransporter activity in neurons (Sun and Murali, 1998, 1999). Cotransporter activity in cortical neurons and astrocytes is elevated when intracellular Ca⁺⁺ increases in the presence of high [K⁺]_o(Schomberg et al., 2001; Su et al., 2000). Because both high [K⁺]_o and elevated extracellular glutamate play important roles in ischemic cell damage, the authors hypothesize that stimulation of the cotransporter in neurons may contribute to overload of intracellular Na⁺ and Cl^- and cell swelling during ischemia. Several studies suggest that the Na⁺-K⁺-Cl^- cotransporter may be involved in ischemic cerebral cell damage. Twenty-four hours of hypoxia decreases cellular adenosine triphosphate (ATP) content and reduces Na⁺-K⁺-ATPase activity, while significantly increasing the Na⁺-K⁺-Cl^- cotransporter activity in rat brain capillary endothelial cells (Kawai et al., 1996). Significant reduction of brain edema by the Na⁺-K⁺-Cl^- cotransporter and Cl^- channel inhibitor torasemide or its derivative also has been observed in focal cerebral ischemia and traumatic brain injury (Staub et al., 1994; Le Bars et al., 1996). However, no study has yet directly demonstrated a role of the cotransporter in ischemic neuronal damage.

The ion pump Na⁺/K⁺-ATPase is a third key mechanism:

ref. These findingssuggest that potassium redistribution by glia only plays a minorrole in the regulation of [K⁺]_o in this model. The major regulator of [K⁺]_o in this model appears to be uptake via a Na⁺/K⁺-ATPase, most likelyneuronal.

And the Blood-brain barrier is also important, since it limits the movement of potassium through the walls of brain capillaries (more info here.)

Perkinjes and Granules and Schwanns, oh my...

2007-04-10T13:27:00.001-07:00

It's tempting to oversimplify things. Like neurons. It would be nice if there were one type of neuron, and all you needed to know about how neurons work could be clearly labelled on a diagram of that one type of neuron. Well, nature LOVES to specialize. So, before getting deeper into how neurons work, I thought it would be good to take a step back and get some vocabulary in place...

The Basics

From University of Washington's 'Neuroscience for kids': Neurons come in many different shapes and sizes. Some of the smallest neurons have cell bodies that are only 4 microns wide. Some of the biggest neurons have cell bodies that are 100 microns wide.

Neurons are similar to other cells in the body because:

Neurons are surrounded by a cell membrane.
Neurons have a nucleus that contains genes.
Neurons contain cytoplasm, mitochondria and other "organelles".
Neurons carry out basic cellular processes such as protein synthesis and energy production.

However, neurons differ from other cells in the body because:

Neurons have specialized extensions called dendrites and axons. Dendrites bring information to the cell body and axons take information away from the cell body.
Neurons communicate with each other through an electrochemical process.
Neurons contain some specialized structures (for example, synapses) and chemicals (for example, neurotransmitters).

From "Spiking Neuron Models" by Wulfram Gerstner and Werner M. Kistler (Cambridge University Press 2002): A typical neuron can be divided into three functionally distinct parts, called dendrites, soma, and axon. (see figure at right). Roughly speaking, the dendrites play the role of the `input device' that collects signals from other neurons and transmits them to the soma. The soma is the `central processing unit' that performs an important non-linear processing step: If the total input exceeds a certain threshold, then an output signal is generated. The output signal is taken over by the `output device', the axon, which delivers the signal to other neurons.

It is common to refer to the sending neuron as the presynaptic cell and to the receiving neuron as the postsynaptic cell. A single neuron in vertebrate cortex often connects to more than 10,000 postsynaptic neurons. Many of its axonal branches end in the direct neighborhood of the neuron, but the axon can also stretch over several centimeters so as to reach to neurons in other areas of the brain.

Classes of Neurons

From University of Washington: One way to classify neurons is by the number of extensions that extend from the neuron's cell body (soma).

Bipolar neurons have two processes extending from the cell body (examples: retinal cells, olfactory epithelium cells).

Pseudounipolar cells (example: dorsal root ganglion cells). Actually, these cells have 2 axons rather than an axon and dendrite. One axon extends centrally toward the spinal cord, the other axon extends toward the skin or muscle.

Multipolar neurons have many processes that extend from the cell body. However, each neuron has only one axon (examples: spinal motor neurons, pyramidal neurons, Purkinje cells).

Neurons can also be classified by the direction that they send information.

Sensory (or afferent) neurons: send information from sensory receptors (e.g., in skin, eyes, nose, tongue, ears) TOWARD the central nervous system.
Motor (or efferent) neurons: send information AWAY from the central nervous system to muscles or glands.
Interneurons: send information between sensory neurons and motor neurons. Most interneurons are located in the central nervous system.

From Wikipedia: Purkinje cells (or Purkinje neurons) are a class of GABAergic neuron located in the cerebellar cortex. They are named after their discoverer, Czech anatomist Jan Evangelista Purkyně.

These cells are some of the largest neurons in the human brain, with an intricately elaborate dendritic arbor, characterized by a large number of dendritic spines. Purkinje cells are found within the Purkinje layer in the cerebellum. Purkinje cells are aligned like dominos stacked one in front of the other. Their large dendritic arbors form nearly two dimensional layers through which parallel fibers from the deeper-layer granule cells pass. These parallel fibers make relatively weaker excitatory (glutamatergic) synapses to spines in the Purkinje cell dendrite, whereas climbing fibers originating from the inferior olivary nucleus in the medulla provide very powerful excitatory input to the proximal dendrites and cell soma. Parallel fibers pass orthogonally through the Purkinje neuron's dendritic arbor, with up to 200,000 parallel fibers forming a synapse with a single Purkinje cell. Alternatively, each Purkinje cell only receives a synapse from a single climbing fiber. Both basket and stellate cells (found in the cerebellar molecular layer) provide inhibitory (GABAergic) input to the Purkinje cell, with basket cells synapsing on the Purkinje cell axon initial segment and stellate cells onto the dendrites.

Purkinje cells send inhibitory projections to the deep cerebellar nuclei, and constitute the sole output of all motor coordination in the cerebellar cortex.

Purkinje cells show two distinct forms of electrophysiological activity:

Simple spikes occur at rates of 50 - 150 Hz either spontaneously or and when Purkinje cells are activated synaptically by the parallel fibers, the axons of the granule cells.

Complex spikes are rapid (>300 Hz) bursts of spikes caused by climbing fiber activation, and can involve the generation of calcium-mediated action potentials in the dendrites. Following complex spike activity simple spikes can be suppressed by the powerful complex spike input.

Purkinje cells show spontaneous electrophysiological activity in the form of trains of spikes, which may be important for cerebellar function.

Granule cells refer to tiny neurons (a type of cell) that are around 10 micrometres in diameter. Granule cells are found within the granular layer of the cerebellum, layer 4 of cerebral cortex, the dentate gyrus of the hippocampus, and in the olfactory bulb.

While anatomically similar, granule cells in different brain regions are functionally diverse. For instance, olfactory bulb granule cells are GABAergic and axonless, while granule cells in the dentate gyrus have glutamatergic projection axons. Interestingly, these two populations of granule cells are also the only major neuronal populations that undergo adult neurogenesis, while cerebellar and cortical granule cells do not.

Cerebellar granule cells account for nearly half of the neurons in the central nervous system. Granule cells receive excitatory input from mossy fibers originating from pontine nuclei. Cerebellar granule cells send parallel fibers up through the Purkinje layer into the molecular layer where they branch out and spread through Purkinje cell dendritic arbors. These parallel fibers form thousands of excitatory synapses with Purkinje cells.

Layer 4 granule cells of the cerebral cortex receive driving inputs from thalamus and convey driving inputs largely to supragranular layers 2-3, but also to infragranular layers of the cerebral cortex.

Golgi cells are inhibitory interneurons found within the granular layer of the cerebellum. These cells synapse onto the soma of granule cells. They receive excitatory input from mossy fibres, also synapsing on granule cells, and parallel fibers, which are long granule cell axons. Thereby this circuitry allows for feed-forward and feed-back inhibition of granule cells.

Wrapping things up

ref. Glial cells are nerve cells that don't carry nerve impulses. The various glial (meaning "glue") cells perform many important functions, including: digestion of parts of dead neurons, manufacturing myelin for neurons, providing physical and nutritional support for neurons, and more. Types of glial cells include Schwann's Cells, Satellite Cells, Microglia, Oligodendroglia, and Astroglia. Neuroglia (meaning "nerve glue") are the another type of brain cell. These cells guide neurons during fetal development.

Glial cells are not passive bystanders in cognition, however - they are active players. From "New Insights into Neuron-Glia Communication" by R. Douglas Fields and Beth Stevens-Graham (2002): Two-way communication between neurons and non-neural cells called glia is essential for axonal conduction, synaptic transmission, and information processing and thus is required for normal functioning of the nervous system during development and throughout adult life. The signals between neurons and glia include ion fluxes, neurotransmitters, cell adhesion molecules, and specialized signaling molecules released from synaptic and nonsynaptic regions of the neuron. In contrast to the serial flow of information along chains of neurons, glia communicate with other glial cells through intracellular waves of calcium and via intercellular diffusion of chemical messengers. By releasing neurotransmitters and other extracellular signaling molecules, glia can affect neuronal excitability and synaptic transmission and perhaps coordinate activity across networks of neurons.

From Wikipedia: Schwann cells are a variety of neuroglia that mainly provide myelin insulation to axons in the peripheral nervous system of jawed vertebrates. The vertebrate nervous system relies on this myelin sheath for insulation and as a method of decreasing membrane capacitance in the axon, thus allowing for saltatory conduction to occur and for an increase in impulse speed, without an increase in axonal diameter. Non-myelinating Schwann cells are involved in maintenance of axons and are crucial for neuronal survival.

Schwann cells begin to form the myelin sheath in mammals during fetal development and work by spiraling around the axon, sometimes with as many as 100 revolutions. A well-developed Schwann cell is shaped like a rolled-up sheet of paper, with layers of myelin in between each coil. The inner layers of the wrapping, which are predominantly membrane material, form the myelin sheath while the outermost layer of nucleated cytoplasm forms the neurolemma. Only a small volume of residual cytoplasm communicates the inner from the outer layers. This is seen histologically as the Schmidt-Lantermann Incisure. Since each Schwann cell can cover about a millimeter (0.04 inches) along the axon, hundreds and often thousands are needed to completely cover an axon, which can sometimes span the length of a body. The gaps between the Schwann cell covered segments are the Nodes of Ranvier, important sites of ionic and other exchanges of the axon with the extracellular liquid. Unlike oligodendrocytes, myelinating Schwann cells provide insulation to only one axon (see image). This arrangement permits saltatory conduction of action potentials which greatly speeds it and saves energy.

From Wikipedia: Nodes of Ranvier are regularly spaced gaps in the myelin sheath around an axon or nerve fiber. About one micrometer in length, these gaps expose the axonal membrane to the extracellular fluid. (The myelin sheath is the fatty tissue layer coating the axon.)

The myelin sheath helps speed the neural impulse by insulating the electrical current and making it possible for the impulse to jump from node to node, a process known as saltatory conduction, as opposed to traveling down the axon in tiny increments.

An action potential is the sharp electrochemical response of a stimulated neuron, a neuron whose membrane potential has been changed by a nearby cell, cells, or an experimentor. In an action potential, the cell membrane potential changes drastically and quickly as ions flow in or out of the cell. The action potential "travels" from one place in the cell to another, but ion flow occurs only at the nodes of Ranvier. Therefore, the action potential signal "jumps" along the axon, from node to node, rather than propagating smoothly, as they do in axons that lack a myelin sheath. This is due to clustering of voltage-gated Na⁺ and K⁺ ion channels at the Nodes of Ranvier.

Unmyelinated axons do not have Nodes of Ranvier; voltage gated ion channels in these axons are considerably less ordered and spread over the entire membrane surface.

Yale's Neuron Database

From Yale's Neuron Database for Vertebrates:

Subdivision	General Region	Specific Region	Neurons
Forebrain	Archicortex	Dentate	Dentate granule cell
		Hippocampus	CA1 pyramidal neuron
			CA1 oriens alveus interneuron
			CA3 pyramidal neuron
	Basal Ganglia	Neostriatum	Neostriatal cholinergic interneuron
			Neostriatal spiny neuron
		Substantia Nigra	Nigral dopaminergic cell
	Diencephalon	Retina	Retinal photoreceptor
			Retinal ganglion cell
			Retinal bipolar cell
		Thalamus	Thalamic relay neuron
			Thalamic reticular neuron
	Neocortex	Visual & Motor	Neocortical pyramidal neuron: deep
			Neocortical pyramidal neuron: superficial
			Neocortical basket cell
	Olfactory Epithelium	Olfactory Epithelium	Olfactory receptor neuron
	Olfactory Bulb	Olfactory Bulb	Olfactory bulb mitral cell
			Olfactory bulb granule cell
			Olfactory bulb periglomerular cell
	Paleocortex	Olfactory Cortex	Olfactory cortex pyramidal neuron
			Olfactory cortex interneuron: superficial
			Olfactory cortex interneuron: deep
Mesencephalon
Metencephalon	Cerebellum	Cerebellum	Cerebellar granule cell
			Cerebellar purkinje cell
	Inner Ear	Cochlea	Hair cell (auditory)
		Vestibular Organ	Hair cell (vestibular)
	Cochlear Nucleus	Anterior Ventral CN	CN bushy cell
		Posterior Ventral CN	CN octopus cell
		Dorsal CN	CN pyramidal (fusiform) cell
Myelencephalon
Spinal Cord	Segment	Ventral Horn	Spinal motor neuron
			Spinal Ia interneuron

The Neuron Doctrine

The neuron doctrine is the now fundamental idea that neurons are the basic structural and functional units of the nervous system. The theory was put forward by Santiago Ramón y Cajal in the late 19th century. It held that neurons are discrete cells (not connected in a meshwork); that neurons are genetically and metabolically distinct units; that they have cell bodies, axons and dendrites; and that neural transmission goes only in one direction, from dendrites toward axons. (ref.)

The Neuron Doctrine, Redux

In the article "The Neuron Doctrine, Redux" (Bullock, T.H., Bennett, M.V.L., Johnston, D., Josephson, R., Marder, E., Fields R.D. 2005), the authors present a compelling case for expanding the scope of the original neuron doctrine.

It turns out that electrical synapses are more common in the central nervous system than previously thought. They occur where the synaptic gap between two neurons is narrower than usual (2-4 nm), allowing special ion channels called 'connexons' that exist in the axon's synaptic region and the dendrite's synaptic region to connect to each other, creating ion channels that span the membrane of both the axon and dendrite. The ion channels allow the flow of polarizing ions and signaling molecules to flow directly from the transmitting neuron to the recieving neuron. (ref.)

It also turns out that dendrites, like axons, have voltage-gated ion channels and can generate electrical potentials that carry information to and from the soma. This challenges the view that dendrites are simply passive recipients of information and axons the sole transmitters. It also suggests that the neuron is not simply active as a single element, but that complex computations can occur within a single neuron. (ref.)

And it's also important not to get too focused on single neurons. The single neuron spike record as indicator for a binary neural code persisted in mainstream neurophysiology until finally, in the late 1980s, it was challenged by the discovery of synchronized electrical wave electrical activity as a highly specific coordinating link among distributed neurons. (ref.)

Slow electrical potentials, action potentials initiated in dendrites, neuromodulatory effects, extrasynaptic release of neurotransmitters, and information flow between neurons and glia all contribute to information processing. (Science Magazine)

Summary

Ref: `Real' neurons are extremely complex biophysical and biochemical entities. Before designing a model it is therefore necessary to develop an intuition for what is important and what can be safely neglected. The Hodgkin-Huxley model describes the generation of action potentials on the level of ion channels and ion current flow. It is the starting point for detailed neuron models which in general include more than the three types of currents considered by Hodgkin and Huxley.

Electrophysiologists have described an overwhelming richness of different ion channels. The set of ion channels is different from one neuron to the next. The precise channel configuration in each individual neuron determines a good deal of its overall electrical properties. Synapses are usually modeled as specific ion channels that open for a certain time after presynaptic spike arrival.

The geometry of the neuron can play an important role in synaptic integration because the effect of synaptic input on the somatic membrane potential depends on the location of the synapses on the dendritic tree. Though some analytic results can be obtained for passive dendrites, it is usually necessary to resort to numerical methods and multi-compartment models in order to account for complex geometry and active ion channels.

Baby, you're a knockout - RNA interference and Transgenic organisms

2007-03-15T13:14:00.001-07:00

One of the most powerful ways to find out what a gene does is to disable the gene in a seed, an ova or an embryo, grow the resulting 'transgenic' organism and find out what functions are missing. This approach is being done for mustard seed and mice in order to identify the function of each gene in these 'model organisms'. Since many genes are re-used in other organisms, it is hoped that determining the function of each of the 29,500 mustard seed genes will shed insight into the genetics of other plants, and that determining the function of the murine genes in transgenic mice will translate into knowledge of the genetics of other mammals, like humans.

1000s of varieties of mustard

From the NSF: To create a gene knockout, scientists use a bacterium called Agrobacterium to insert a code that tells a specific gene to turn off. According to Ecker, this process of T-DNA integration has been carried out for well over 25 years, but this study provides a new perspective on using the technique to analyze gene function.

Some genes, it turns out, contain certain features that mark them as favored targets of inactivation. Additionally, Ecker and his colleagues have discovered that fewer inactivations occur near the centromeres -- the thinner gene-poor regions of the chromosome. "These results provide significant new information in both the areas of functional genomics and basic plant biology," says Ecker.

Of Mice and Men

There's an excellent article in The Scientist from 2002 that provides a history of the development of this technology, and this article provides details on the painstaking procedures that were used to create transgenic mice. But all that was before RNAi really took off.

From another great article in The Scientist from 2003: We've searched for decades for a way to knock out genes effectively," Sharp says. "We have about 35,000 different genes and have determined the function of only about 500 of them using an incredibly painful, expensive knockout technology. We won't ever understand the remaining functions with the existing technology."

From NeurologyReviews.com (Jan 2005): Dr. Henry Paulson explained that RNAi has revolutionized investigation of gene activity in the lab. Simply by introducing the appropriately sequenced double-stranded RNA into a cell culture or animal model, it is possible to “knock down” production from any gene of interest. “It’s now very clear that the most potent way to silence a gene is through a small double-stranded intermediate,” he said. The first demonstration of RNAi in mammals was in 2001, and since then, the field has exploded. In that seminal study, the nuclear envelope gene lamin was silenced. “Not only was it extremely potent but there were very few of the nonspecific effects seen with previous antisense technology,” he elaborated, referring to a related but entirely artificial technique. “The double-stranded RNA used like this does a heck of a lot better job.”

When RNA itself is directly introduced to the cell, however, it is eventually degraded. This may be useful in the lab for short-term studies, but for disease therapy, longer-term effects are desired. The alternative is delivering DNA that codes for the RNA, via a viral vector. “The advantage is that you have sustained expression within the cell of the double-stranded RNA you want,” said Dr. Paulson. “Can this work in the brain? Yes.”

2006 Nobel Prize in Medicine

The 2006 Nobel Prize in Medicine was awarded to Craig C. Mello and Andrew Z. Fire for their discovery of RNA interference - gene silencing by double-stranded RNA. (illustrated presentation - check it out!)

From Craig C. Mello's HHMI web page:

For decades, RNA molecules have been regarded as little more than DNA's messengers, ferrying the genetic code to the cell's protein-building factories. Craig Mello's research has helped to establish that certain RNA molecules play a far more impressive role in the cell. In a groundbreaking discovery, he found that short snippets of RNA can silence the expression of targeted genes. This phenomenon, called RNA interference, not only has become an indispensable means for studying gene function but has been found to be a normal part of gene regulation during embryonic development and may play a role in cancer and other diseases.

Craig was looking for an effective way of blocking the expression of specific genes in the developing embryo as a way to study their function. Working with C. elegans embryos, he injected RNA into the worms and was surprised to find that the interference effect was far more robust than expected. The RNA interference spread from cell to cell throughout the worm's body, regardless of the site of injection, and was transmitted from one generation to the next. "This was unheard of," Mello explained. "Something extremely interesting was going on but we didn't know what it was." After further studies conducted in collaboration with Andrew Fire of the Carnegie Institution of Washington, the pair revealed in a paper published in Nature in 1998 that the gene-silencing effect was in fact caused by double-stranded RNA.

From Stanford's web page 'The Secret Life of RNA':

The process of RNAi hinges on RNA’s Velcro-like nature. Like its sibling DNA, RNA is composed of a series of subunits called nucleotides designated A, U, G and C strung together in a chain. The series of letters making up each molecule determines what protein it generates and also allows it to clasp other RNA molecules or DNA. An A on one RNA molecule will find its match with a U on the other molecule and the C’s and G’s pair up. A molecule with the sequence ACUG, for example, would pair up with the opposing sequence UGAC.

Although the fine details are slightly different in each organism, the broad brushstrokes of RNAi go like this: RNA molecules up to many thousands of letters long enter the cell where a protein called Dicer chops it into units of 21 or 22 letters. These chunks are called small interfering RNAs or siRNA. They conglomerate with proteins in the cell to make up the RNAi machinery. These complexes bind to the protein-producing RNAs within the cell that have a matching series of A’s, U’s, G’s and C’s. This binding marks the RNA molecule for destruction and eliminates the protein.

From the Novina Lab in Harvard:

In the triggering step of RNAi, Dicer cleaves long dsRNA into several siRNAs each with different sequences though all siRNAs are complementary to the triggering gene. In the effector step of RNAi, helicase activity in the RNA-induced Silencing Complex (RISC) unwinds the duplexed siRNAs and the antisense strand of the siRNA recruits RISC to target mRNA with exactly complementary sequence to the guide strand of the siRNA. An endonuclease in RISC degrades the targeted mRNA by cleavage of the mRNA at a position on the mRNA between the 10th and 11th nucleotides of the guide strand of the siRNA. The 3’ mRNA cleavage fragment possesses a 5’phosphomonoester.

From the Dana-Farber cancer institute: "Silence is golden" by Richard Saltus:

Unlike knockout mice, RNAi technology doesn't totally block genes' ability to make proteins — known as gene "expression" — but can reduce it to a very low level. Nevertheless, researchers use the terms gene "silencing" and "inactivation" when referring to RNAi.

"In simple terms, RNAi lets you inactivate any gene you're interested in at any time. This has rapidly become an essential and powerful tool," says Barrett Rollins, MD, PhD, Dana-Farber's chief scientific officer. "The specificity and flexibility of RNAi guarantee that it will become a standard and essential component of everyone's scientific toolbox."

In biology labs everywhere, RNAi tools are changing the way science is done. With a focus on cancer, scientists at Dana-Farber, along with colleagues at the Broad Institute of the Massachusetts Institute of Technology and Harvard University, have deployed RNAi technology in a hunt for genes they call cancer's "Achilles' heels" – genes behaving abnormally that tumors depend on to grow, survive, and progress. Using a specific type of RNAi tool called "short hairpin RNAs," or shRNAs, scientists can sequentially turn off genes in thousands of different cancer cells to find out which genes, when silenced, cause the cells to weaken or die. Identifying such genes would be the starting point for developing new drugs to target them.

Viral delivery of short hairpin RNAs:

Carl Novina, MD, PhD, used harmless viruses called lentiviruses to transport the RNA-interceptors into cells. "The advantage is that lentiviruses infect not just dividing cells, as many others do, but non-dividing cells where we want to use RNAi to find a gene's function," says Novina. In addition, a gene silenced by an RNAi-carrying lentivirus stays silenced — a contrast to some other delivery techniques whose effects are transient. "It is now possible to use a lentivirus to infect an embryonic stem cell and generate a mouse in which the short hairpin RNA is expressed continuously," Novina says. "With the advent of specialized lentiviruses, it is possible to turn RNAi on and off at specific times to discover when genes function," he adds.

Video of RNA Interference (from the journal Nature)

Membrane Fusion: from viruses to Gene Therapy and RNA Interference

2006-10-07T21:47:00.000-07:00

The previous blogs have gotten into how synaptic vessicles fuse with the synapse membrane. Similar mechanisms are used by viruses to enter healthy cells, and are now being harnessed for the latest genetic medical treatments: Gene Therapy and RNA Interference. Some very cool stuff happening in this area.

Research into the HIV virus led to some of the first breakthroughs in understanding the membrane fusion mechanism. Retroviruses are particularly adept at invading a wide variety of different human cells, which makes them good models to study for gene therapy. Lifecycle of the virus provides a good intro to how viruses work. The HIV virus anchors itself to a special protein (CD4) on the surface of the helper T cell. This causes the viral membrane to fuse with the host cell's membrane. It's called a Lentivirus (Lenti is latin for "slow").

From the University of Birmingham:

HIV as a Lentiviral Vector in Gene Therapy
From Kenyon College's web site:
What is gene therapy?
The aim of gene therapy is to modify the genetic material of living cells for therapeutic purposes (Amado and Chen, 1999). Gene therapy involves the insertion of a functional gene or another molecule that contains and information sequence into a cell to achieve a therapeutic effect. Thus, the gene serves as a drug (Lasic, 1997). There are two types of gene therapy: somatic cell and germ line. Somatic cell gene therapy is the only technique now in use. The purpose of the procedure is to eliminate the clinical consequences of a disease and the inserted gene is not passed on to the patient's offspring. In germ line gene therapy a healthy gene is inserted into the fertilized egg of an animal that has a genetic effect. Every cell that develops from this egg, including the reproductive cells, will have the new gene. However, there are very serious social and ethical considerations with this type of gene therapy (Nichols, 1998).
Before 1996 scientists relied mainly on modified retroviruses such as Moloney murine leukemia virus when gene transfer into the chromosomes of target cells was needed, and adenovirus vectors when such integration was not needed. However, there has been little success in gene transfer with such virus vectors because even though the vectors can enter into their target cells, the cells need to be dividing, so that their nuclear membrane are broken down, for the gene to enter and integrate into the chromosome (Sikorski and Peters, 1998; CFAR at UC San Diego). However, scientists soon realized that members of the subfamily lentivirus, such as the retrovirus human immunodeficiency virus (HIV), would have the same ability to transfer genetic material into the genomes of cells, but could do this with non-dividing, dormant cells in vivo and growth-arrested cells in vitro (Amado and Chen, 1999; CFAR at UC San Diego). Exploring this new method of gene therapy has been the work of many labs in the past few years.

What are lentiviral vectors?
Lentiviral vectors are a type of retrovirus that can infect both dividing and nondividing cells because their preintegration complex (virus “shell”) can get through the intact membrane of the nucleus of the target cell. Lentiviruses can be used to provide highly effective gene therapy as lentiviruses can change the expression of their target cell's gene for up to six months. They can be used for nondividing or terminally differentiated cells such as neurons, macrophages, hematopoietic stem cells, retinal photoreceptors, and muscle and liver cells, cell types for which previous gene therapy methods could not be used. HIV is a very effective lentiviral vector because it has evolved to infect and express its genes in human helper T cells and other macrophages. The only cells lentiviruses cannot gain access to are quiescent cells (in the G0 state) because this blocks the reverse transcription step (Amado and Chen, 1999).
...
Uses for HIV Lentiviral Vectors
Scientists have recently been using the HIV lentiviral vector to repair neurons. HIV is also being developed as a delivery system to provide successful gene therapy in many diseases such as metabolic diseases, cancer, viral infection, cystic fibrosis, muscular dystrophy, hemophilia, retinitis pigmentosa, and maybe even Alzheimer’s disease (Adler, Gifford, and Sumner; Naldini et al.; Amado and Chen, 1999; Planelles).
Concerns With Using HIV Lentiviral Vectors
There is still concern with using lentiviral vectors for safety reasons. One concern involves the possibility that the HIV could self-replicate and could be produced during manufacture of the vector in the packaging cell line or in the target cells by a process of recombination. Thus, the person undergoing gene therapy would also be infected with HIV in addition to the new therapeutic gene. A self-replicating infectious vector could cause cancer by inserting itself into the host genome and activate a neighboring proto-oncogene, thus causing mutagenesis (Amado and Chen, 1999).

Because scientists have shown that lentiviruses, such as HIV, are successful and efficient gene delivery vehicles, the field has now turned its attention to producing vectors with built-in safety features to prevent the development of replication competent lentiviruses (RCL). However, even the earliest studies with HIV lentiviral vectors did not generate RCL in vitro or in vivo (Amado and Chen, 1999), but precautions are still very important.
...
Use of Non-Human Lentiviral Vectors
By using non-human lentiviruses, scientists hope to bypass the issue of host infection by the gene therapy vector. Researchers are developing non-human lentiviruses such as the feline immunodeficiency virus (FIV) to be used in gene therapy (Amado and Chen, 1999).

Lots more excellent info at this site - worth checking out.

There's a wonderful animation at Hybrid Medical Animation that shows viral attachment to a cell via a glycoprotein in its membrane and the resulting membrane fusion in action. Highly recommended.

The membrane fusion shown in the animation was recently seen live at the Brookhaven National Laboratory:
Molecular Details of Cell Membrane Fusion Revealed
The diffraction pattern showed that, when the two membranes fuse, they form an hourglass-shaped structure called a stalk, confirming theoretical predictions. When the stalk stretches further, it creates a connecting bridge between the membranes. This connection then enlarges, and the two membranes ultimately become one single membrane.

The Nolan Lab at Stanford has a web page that goes into detail on some of the retroviral systems being explored as alternatives to HIV for Gene Therapy:

Non-RCR vectors
The production of viral particles in a producing cell line that will be able to infect target cells, but won’t be able to form a replication-competent recombinant (RCR) and subsequently infect other target cells is a feature behind the development of HIV-1 based vectors.

When HIV-1 based vectors are used, the goal has been to diminish the probability of a recombination event that will give rise to full-length replicative viral DNA. This has been accomplished by separating the structural and delivery constructs onto three different plasmids. The regulatory/accessory genes of HIV-1, specifically Nef, Vpr, Vpu, Vif and Tat have been shown to be largely dispensible for gene delivery to most cell types.
...
Sin vectors
Although the recombination event possible between three independent plasmids is extremely small, ways to decrease even further this probability when dealing with HIV-1 based vectors have been undertaken in the plasmids presented at this site. This is the basis of the development of self-inactivating vectors or SIN vectors.

Basically, a chunk of the virus that harbors the major transcriptional functions of the HIV genome is removed. The lack of active viral promoter avoids both the possible transcription of the viral sequence and detrimental effects on eukaryotic gene expression.

To get a better understanding of how these retroviruses do their membrane fusion stuff, you need to get insight into the Structures of Retrovirus Surface Proteins. This is what Dr. Deborah Foss has been investigating: Through x-ray crystallography, her team has found similarities between the surface proteins that two different retroviruses use to fuse with cell membranes:

We have recently determined the structure of the portion of a feline leukemia virus that binds a phosphate transporter as its cell-surface receptor, and we compared this structure to that of a murine leukemia virus ... which binds a basic amino acid transporter. In this figure, the polypeptide chain is represented by a ribbon, and carbohydrates and disulfide bonds are shown as balls-and-sticks. The cores of the two structures, shown in blue, are very similar. In contrast, the regions labeled "VRA" and "VRB" for "variable regions A and B," are structurally very different between the feline and murine viruses. These structures illustrate how diverse receptor-binding specificities interface with the conserved scaffolds and the shared cell-entry mechanism of this retrovirus group.

The potential for Gene Therapy
From Indiana State U.:
The most common techniques utilized in gene therapy studies is the introduction of the corrected gene into bone marrow cells, skin fibroblasts or hepatocytes. The vectors most commonly utilized are derived from retroviruses and utilize only the transcriptional promoter regions of these viruses (the LTRs) to drive expression of the gene of interest. The advantage of retroviral-based vector systems is that expression occurs in most cell types.

A number of human inherited disorders have been corrected in cultured cells and several diseases (e.g. malignant melanoma and severe combined immunodeficiency disease, SCID) are currently being treated by gene therapy techniques indicating that gene therapy is likely to be a powerful therapeutic technique against a host of diseases in coming years.

The first successful examples of this type of retro-viral gene therapy were reported in August.

Non-viral Gene Therapy Methods
From Biology News:
Scientists have used viruses as a gene delivery mechanism for more than 20 years because of their adeptness at getting inside cells and inserting themselves in DNA. But efficiency comes at a price. Gene therapy trials have been halted because of major complications, including deaths. As examples, one patient died because of his immune response to an adenovirus and three children in another study developed leukemia because the virus inserted itself upstream of a cancer-causing gene.

"With viruses, you don't have control," says Dr. Kaminski. "People have tried to modify viruses for site-specific integration and have not been very successful. Once they get into the cell, they can insert wherever they want."
...
A jumping gene first identified in a cabbage-eating moth may one day provide a safer, target-specific alternative to viruses for gene therapy, researchers say. They compared the ability of the four best-characterized jumping genes, or transposons, to insert themselves into a cell's DNA and produce a desired change, such as making the cell resistant to damage from radiation therapy.

They found the piggyBac transposon was five to 10 times better than the other circular pieces of DNA at making a home and a difference in several mammalian cell lines, including three human ones.

"If we want to add a therapeutic gene, we can put it within the transposon and use it to deliver the gene into the cell," says Dr. Joseph M. Kaminski, radiation oncologist at the Medical College of Georgia Cancer Center and a corresponding author on research published the week of Sept. 25 in the online Proceedings of the National Academy of Sciences Early Edition. "You can use these wherever retroviruses have been used."

Hybrid Viral/SyntheticGene Therapy Methods
From The University of Illinois:
We are developing a new class of gene delivery vectors by combining viral and synthetic components to produce hybrid, active nanostructures. Recombinant viruses by themselves are highly efficient vectors, but suffer from serious safety concerns, difficulty with redirecting cell specificity, and expensive production and purification. Polymeric vectors are potentially safer, cheaper and more versatile, but in their current form lack the efficiency needed for clinical application. Hybrid viral/synthetic nanovectors may be designed to exhibit several of the advantages (and possibly avoid disadvantages) of both types of vectors.

RNA Interference
Whereas Gene Therapy can be used to introduce new or missing genes into cells in the human body, RNA Interference can be used to suppress the expression of genes in cells. It uses the same delivery mechanism as gene therapy, but a different type of payload. From Neurology Reviews January 2005 issue:
RNAi is a natural phenomenon, found in organisms from yeasts to plants to mammals. Its normal function appears to be twofold: to protect against viruses and other exogenous gene sources, and to regulate gene expression. Both functions rely on the same machinery, which detects double-stranded RNA molecules in the cell, and prevents their translation into protein. “RNAi essentially shoots the messenger,” said Dr. Paulson, by either destroying the double-stranded RNA or silencing it without destruction.

A key event in the process of RNAi is detection and cleavage of double-stranded RNA by an enzyme appropriately named Dicer, in a multiprotein complex called RISC (RNA-induced silencing complex). The resulting small RNA fragments then serve as templates for the detection and cleavage of additional RNAs with the same sequence. This is the basis for the therapeutic application of RNAi: By introducing a double-stranded RNA that matches the gene to be silenced, one can effectively prevent protein synthesis from that gene for an extended period of time.

Dr. Paulson explained that RNAi has revolutionized investigation of gene activity in the lab. Simply by introducing the appropriately sequenced double-stranded RNA into a cell culture or animal model, it is possible to “knock down” production from any gene of interest. “It’s now very clear that the most potent way to silence a gene is through a small double-stranded intermediate,”
...
When RNA itself is directly introduced to the cell, however, it is eventually degraded. This may be useful in the lab for short-term studies, but for disease therapy, longer-term effects are desired. The alternative is delivering DNA that codes for the RNA, via a viral vector. “The advantage is that you have sustained expression within the cell of the double-stranded RNA you want,” said Dr. Paulson. “Can this work in the brain? Yes.”

Resources
Indiana State U. has a very good Introduction to Molecular Medicine web page that provides a lot of useful info, including good descriptions of some of the key concepts (cDNA, etc.).

Biosynthesis and role of filoviral glycoproteins - the article that the great picture of membranes fusing at the top of this blog came from. Discusses research into the molecular mechanisms used by the Ebola virus.

U. of Virginia: Membrane Fusion in Viral Infection

Synaptic Vesicles - Message in a bottle

2006-09-05T16:49:00.000-07:00

Previous blog entries have covered what Neurotransmitters are, and how synaptic receptors use these molecules as triggers for complex actions once they have crossed the synapse. This blog entry explores the other side of the synaptic cleft, where the neurotransmitters are stored and released.

Nature has developed some amazing machinery to make synapses fire quickly. Relying on the cell nucleus to generate the molecules that act as neurotransmitters when they are needed would be far too slow to achieve the kind of speed required to power thought. Instead, these molecules are made ahead of time, before they are needed, and are kept bottled up in spherical containers called 'vesicles', waiting for the instant that they need to be released. The picture that is evolving on how synapses actually manage this feat is quite fascinating. And, once again, that super cool molecule called 'clathrin' plays a major role...

From http://www.hhmi.org/research/investigators/sudhof.html:
Neurons communicate with each other by synaptic transmission at specialized intercellular junctions called synapses. During synaptic transmission, a presynaptic neuron releases a chemical neurotransmitter that is then recognized by the postsynaptic neuron.

The electrical impulses, called action potentials, cause the vesicles to fuse with the nerve cell membrane and spill their contents into the synapse. The neurotransmitters then activate receptors on the other side of the synapse, essentially allowing the action potential to “jump the gap” to the next nerve cell.

Neurotransmitter release is triggered when an electrical impulse that travels down the neuron's axon, called an action potential opens voltage-gated Ca2+ (calcium ion) channels and Ca2+ flows into the presynaptic terminal. Ca2+ triggers neurotransmitter release by stimulating the fusion of synaptic vesicles ( [tiny spheres] that are filled with neurotransmitters) with the presynaptic plasma membrane at the active zone (a specialized plasma membrane section that marks the synapse). Released neurotransmitters then elicit a postsynaptic signal. Synaptic transmission occurs by this mechanism in all synapses, but the specific properties of synaptic transmission vary among synapses.

From the NIH:Likened to soap bubbles merging, or bubbles bursting at the surface of boiling water, membrane fusion has attracted heightened interest among neuroscientists in recent years. The family of proteins involved, SNARES (Soluble NSF Attachment protein REceptor), have been conserved through evolution, performing similar functions even in primitive organisms like yeast and fruit flies. Some of the fusion proteins are embedded in the vesicle and the cell wall membranes; others float freely within the nerve terminal, or axon.

The entire neurotransmission performance — from electrical signal to receptor binding — lasts less than a thousandth of a second, and is repeated billions of times daily in each of the human brain's 100 billion neurons. So membrane fusion mechanisms may hold clues about what goes wrong in disorders of thinking, learning and memory, including schizophrenia and other mental illnesses thought to involve disturbances in neuronal communication.

The Synaptic Vesicle In Action!
From http://origins.swau.edu/papers/complexity/trilo/gifs/vesicles.html:

1. The synaptic vesicle accumulates hydrogen ions at the expense of ATP. The hydrogen ions are then exchanged for a neurotransmitter (red) such as acetylcholine, by a specific antiport protein.
2. As the vesicle becomes charged with the neurotransmitter, it is picked up by a cytoplasmic transport protein and carried through the cytoplasm to the synaptic region of the neuron.
3. The filled vesicle is docked in the region of the synapse, where it awaits a nerve stimulation.
4. Triggered by an influx of calcium ions, the vesicle releases its charge of neurotransmitter to the synapse, passing the impulse on to the post-synaptic cell.
5. The empty vesicular membrane is surrounded by cytoplasmic protein molecules called clathrin (blue), capturing the vesicle for reuse. The clathrin forms a cage coating the entire vesicle. The vesicle then travels back away from the membrane into the cytoplasm and loses its protective cage.
6. The vesicle again begins to accumulate hydrogen ions the cycle is repeated.

Nothing is left to chance in this sequence. Each step governed by specialized molecules.

From http://www.cnsforum.com/imagebank/item/vesicle_fusion/default.aspx :
Fusion of a synaptic vesicle with the pre-synaptic membrane

Neurons communicate with their target cells primarily through the regulated fusion of synaptic vesicles with the nerve terminal membrane and subsequent release of chemical neurotransmitter into the synaptic cleft. Synaptic vesicles move down the axon and bind to release sites on the pre-synaptic membrane via vesicle-membrane proteins (v-SNARE) and target-membrane proteins (t-SNAREs). This SNARE complex interacts with both NSF (N-ethylmaleimide Sensitive Fusion protein) and SNAP (Soluble NSF Attachment Proteins) to form a fusion complex. Action potential propagation induces calcium influx at the pre-synaptic membrane, which, in addition to ATP hydrolysis by NSF, results in disassembly of the SNARE complex and membrane fusion. Following neurotransmitter release, synaptic vesicle membrane components are recycled via an endocytic process.

More from http://www.hhmi.org/research/investigators/sudhof.html

Model for the functions of SNARE proteins, complexins, and synaptotagmins 1 and 2 in synaptic vesicle exocytosis.

In docked vesicles (left), SNAREs and synaptotagmins are not engaged in direct interactions. During priming (center), SNARE complexes form, and synaptotagmins constitutively associate with the assembled SNARE complexes. The approximation of the synaptic vesicle and plasma membranes forced by SNARE complex assembly is proposed to create an unstable intermediate that is shown as a fusion stalk, but could have other structures. Subsequently, complexins (green) are bound to fully assembled complexes (right), and calcium influx (right) destabilizes the fusion intermediate by triggering the C2-domains of synaptotagmins to associate with, and partially insert into, the phospholipids. This is proposed to cause a mechanical perturbation that opens the fusion pore. Note that SNARE complex assembly in priming (center) is suggested to be reversible, whereas calcium triggering is not.

At a synapse, pre- and postsynaptic compartments are linked by trans-synaptic cell adhesion molecules that in turn are coupled to the presynaptic release machinery or to postsynaptic receptors. A decade ago, we identified candidate trans-synaptic cell adhesion molecules called neurexins and neuroligins. Neurexins are thought to be presynaptic, are expressed in two principal forms, a- and ß-neurexins, and are highly polymorphic due to extensive alternative splicing. Neuroligins are primarily postsynaptic and are also alternatively spliced; their importance is highlighted by the finding that neuroligin mutations are pathogenic in a subset of patients with familial autistic syndrome.

Neurexins bind to neuroligins to form heterophilic intercellular junctions at the
synapse; this binding is tightly regulated by alternative splicing of neurexins and—as we recently observed—of neuroligins, resulting in a trans-synaptic splice code. Moreover, recent experiments with mutant mice revealed that neurexins and neuroligins are not required for the establishment of initial synaptic contacts, but are both essential for the regular function of synapses. Mice with mutant neurexin or neuroligin genes form ultrastructurally normal synapses. In the mutants, however, synaptic transmission is severely impaired, such that the mutant mice die at birth. Overall, these studies showed that neurexins and neuroligins are genuine synaptic cell adhesion molecules that guide synapse formation not by triggering the assembly of synaptic junctions but by recruiting crucial components of the pre- and postsynaptic machinery.

Neurotransmitter Release
To identify key molecules involved in release, we initially set out to characterize the proteins of synaptic vesicles and of the active zone. We then used biochemical and biophysical methods to determine the properties and atomic structures of these proteins, and targeted mouse mutants to examine their functions. Although many questions remain, this combination of approaches has elucidated fundamental mechanisms underlying key aspects of neurotransmitter release (e.g., Ca2+ triggering of fast synaptic vesicle fusion).

Synaptic vesicle fusion is at least in part mediated by the assembly of three synaptic SNARE proteins—the vesicle protein synaptobrevin/VAMP and the plasma membrane proteins SNAP-25 and syntaxin/HPC-1—into a tight complex. Syntaxin also interacts with another essential fusion protein, Munc18-1. SNARE proteins and Munc18-1 perform multiple functions that are exquisitely regulated. For example, during fusion, syntaxin changes from a closed into an open conformation. We recently showed in mice that permanent "opening" of syntaxin by mutagenesis destabilizes synapses, leading to massive epilepsy. As another example, synaptobrevin is required for both spontaneous and evoked synaptic vesicle fusion, but recent data reveal that the mechanisms by which synaptobrevin acts in these two forms of fusion differ. In addition to this dual function in exocytosis, synaptobrevin is also required for normal fast endocytosis of vesicles. These findings suggest an unexpectedly economical organization of the secretory machinery in which different steps are mediated by the same molecules via different mechanisms.

At the synapse, Ca2+ triggers both a fast component and a slow component of release. The fast component is induced by Ca2+ binding to the synaptic vesicle proteins synaptotagmin 1 and 2. Recent data show that these two synaptotagmins act similarly in stabilizing resting synapses and in triggering fast release upon Ca2+ binding.
...
Active-zone proteins not only serve as a receptacle of synaptic vesicles for fusion but also regulate synaptic vesicle fusion during plasticity. Key active-zone proteins for both functions are Munc13s and RIMs, multidomain proteins that bind to each other and to other active-zone and synaptic vesicle proteins. Many isoforms of Munc13s and RIMs with differential properties are expressed, but all isoforms appear to function in release. Recent results, for example, demonstrated that deleting one RIM isoform, RIM1a, leads to discrete changes in both vesicle priming and the plasticity of release, whereas deletion of multiple isoforms almost completely abolishes release. These and other findings have led to the view of the active zone as a protein mosaic whose precise composition is a key determinant of the properties (for example, strength and plasticity) of a synapse.
...
Several facts — for example, the critical role of the presynaptic protein a-synuclein in the pathogenesis of Parkinson's disease, or the transport of the cell-surface protein APP (the amyloid-ß precursor protein that is critical for the pathogenesis of Alzheimer's disease) into presynaptic nerve terminals — point to a presynaptic dysfunction in at least some neurodegenerative disorders. To approach this problem, we have begun to study the normal synaptic function of APP and synuclein. Our studies have uncovered an unexpected role for APP in gene expression, and led to a description of a powerful activity of synucleins in suppressing neurodegeneration. Strikingly, we found that synucleins genetically interact with CSPa (cysteine string protein a), a synaptic vesicle cochaperone protein. CSPa acts as a proprietary chaperone on synaptic vesicles whose deletion causes massive neurodegeneration. Moderate overexpression of synucleins abolishes the neurodegeneration in CSPa-deficient mice, while deletion of endogenous synucleins accelerates the neurodegeneration.

From the NIH: Molecular Minuet of Membrane Fusion Proteins Unveiled

Just before a neuron sprays a neurotransmitter into the synapse, mercurial molecules perform a secret dance that fuses the vesicle membrane with the cell wall membrane. Proteins change their shapes and locales, as their Velcro-like extensions intertwine to conjure a momentary dragon. This highly charged core complex melds the membranes, then vanishes. In the March 23, 2000 issue of Nature, NIMH grantees Drs. Richard Scheller, William Weis and colleagues at Stanford University reveal, for the first time, the atom-by-atom, 3-D structure and cagey choreography of a lead hoofer in this act, the Sec1-syntaxin1a complex.
...
Scheller, Weis and doctoral student Kira Misura were especially interested in a complex created when two proteins bind together: the free-floating SNARE regulator nsec1, and the target membrane's sharply-bent, helical SNARE, syntaxin1. Formation of the complex is the first act in the membrane fusion ballet. To reveal the complex's secret moves, the researchers examined its crystalline structure using a type of subatomic particle accelerator called a synchrotron. The mile-long accelerator generates very intense x-ray beams used to resolve objects as small as atoms, and capture snapshots of the shapes of molecules at different stages of chemical reactions.

Based on the revealed physical properties, as well as genetic and biochemical evidence, the investigators propose that sec1/syntaxin1 complex communicates with Rab, a G protein on the vesicle membrane, and Rab-E, a free-floating cousin, to recognize and guide the neurotransmitter-filled sac to its appointed fusion site on the target membrane. They further propose that syntaxin1a and Sec1 collaborate with VAMP, a velcro-like vesicle membrane protein, and SNAP-25, a counterpart on the cell's membrane, to bring about fusion itself.

In this model, nSec1 performs a "chaperone-like" role for syntaxin1a, first shielding it from other proteins, and later facilitating its interactions with them. When in its protective posture, nSec1 renders its partner physically incapable of forming stable relationships with other proteins.

The steps to the dance are as follows (See diagram of model below):

A – nSec1 binds tightly to, and cloaks, syntaxin1a, forming a complex that serves as a recognition site for an arriving vesicle.

B – The vesicle's Rab and/or Rab-E proteins recognize the complex, signaling nSec1 to change its shape and move outward, uncovering a key binding region of syntaxin1a, and destabilizing it. Residues from the suddenly exposed binding region signal SNAP-25 to begin making the core fusion complex, using nSec1 as a platform.

C – Syntaxin1a's sharply bent end section moves away from its key binding region, making way for SNAP-25 and VAMP to move in and bind.

D – VAMP/SNAP-25/syntaxin1a combine to form a long, straight, helical bundle, the core complex. This pulls the vesicle and target membranes together, fusing them, and releasing the neurotransmitter. After fusion, an enzyme breaks down the complex and the SNAREs are recycled for a repeat performance.

Discovery sheds light on neurotransmitter release mechanism

Researchers at three medical centers including Vanderbilt have discovered an important mechanism controlling the release of neurotransmitters and hormones. The discovery, reported in the April and May issues of the journal Nature Neuroscience, could lead to new ways to treat pain, Parkinson's disease and perhaps even diabetes.
...
Nature modulates the supply of neurotransmitter through G protein-coupled receptors. These receptors are named for their ability to activate G proteins — actually, to split them into two active parts, an alpha subunit and a beta-gamma subunit.

Four years ago, Hamm and colleagues including Simon Alford, Ph.D., of the University of Illinois at Chicago, and Thomas F. J. Martin, Ph.D., of the University of Wisconsin-Madison, reported that the beta-gamma subunit of an inhibitory G protein blocked neurotransmitter release from large, easily studied nerve cells of the lamprey eel. But they didn't know the mechanism — until now.

In an elegant series of experiments, the researchers showed that the beta-gamma subunit prevents vesicles from fusing with the membrane of the nerve cell. It does this by preventing another protein from binding to the cell's “fusion machinery,” a complex of proteins called SNARE that links the vesicle to the membrane. In particular, the beta-gamma subunit prevents synaptotagmin, a vesicle protein, from binding to the SNAP-25 protein in the SNARE complex.

The researchers identified the site of the subunit's action by injecting tiny amounts of a form of the paralyzing botulinum toxin that chopped off the end of the SNAP-25 protein. When that happened, the subunit could not block fusion, indicating that the chopped-off portion was its binding site.
...
Inhibiting vesicle fusion may be a major way the body regulates the release of a whole array of chemical messengers.

At left, activation of a G protein-coupled receptor releases the beta gamma subunit of an inhibitory G protein. The subunit blocks a vesicle protein, synaptotagmin, from binding to SNAP-25, part of the SNARE complex of proteins (right). This, in turn, prevents the complex from pulling the vesicle and the membrane together. The vesicle is thus unable to fuse to the membrane or spill its contents – neurotransmitter – into the synapse.
by Bill Snyder (May 13, 2005) http://www.mc.vanderbuilt.edu

Neurotransmitters - molecular messages

2006-06-13T19:27:00.000-07:00

You often hear about neurotransmitters in the news and in science magazines in a kind of off-hand way that assumes everyone must surely know what these things are. But, um, what are they, exactly?

From Sandra Ackerman's book "Discovering the Brain": To be recognized as a neurotransmitter, a chemical compound must satisfy six conditions: It must be

synthesized in the neuron,

stored there,

released in sufficient quantity to bring about some physical effect;

when administered experimentally, the compound must demonstrate the same effect that it brings about in living tissue;

there must be receptor sites specific to this compound on the postsynaptic membrane, as well as

a means for shutting off its effect, either by causing its swift decomposition or by reuptake, absorbing it back into the cell.

OK, well, what about hormones? They're chemical messengers too - how are hormones different from neurotransmitters? A hormone, by definition, is a compound produced by an endocrine gland and released into the bloodstream where it can find it's target cells at some distance from it's actual site of release. A neurotransmitter on the other hand is a compound released from a nerve terminal.

When an electrical impulse travels to the end of a nerve cell, it stimulates the terminal of this cell to secrete a chemical signalling molecule at a special junction between nerve cells called a synapse. These nerve terminals are in direct apposition with their target cells to ensure rapid and specific delivery of the signal. This mode of transmission is in general much faster than the endocrine transmission mentioned above.

Both target cells possess receptors for the signalling molecule and may produce identical biochemical responses, it's just a question of the release mechanism that determines whether or not a given molecule is a neurotransmitter or a hormone. So, in the case of adrenaline, it's a hormone when the adrenal gland releases it into the bloodstream and it goes to the heart or the lungs OR it's a neurotransmitter when it is released from a stimulated presynaptic nerve cell and acts on it's neighbouring postsynaptic cell. (ref.).

From Samuel Barondes essay: "Drugs, DNA and the Analyst’s Couch" in “The Next Fifty Years: Science in the first half of the twenty-first century” (Good book! Recommended.)
In 1950, a chemist at Rhône-Poulenc, a French pharmaceutical company, modified the structure of an antihistamine and accidentally created a drug that can eliminate the psychotic thinking of people with schizophrenia. Within a few years the drug became world famous as chlorpromazine (Thorazine), the first truly effective medication for a disabling mental disorder. Because of its dramatic effect, chlorpromazine set a new course for psychiatry for the rest of the twentieth century. (Up to that time, one of the 'recommended' treatments for schizophrenia was lobotomy)

The great success of chlorpromazine stimulated vigorous competition from other pharmaceutical companies. In the 1950s, the search for more antipsychotic medications led to the accidental discovery of two other types of phsychiatric drugs. First Geigy, a Swiss pharmaceutical company, came up with a modified version of one of its antihistamines that, although useless against psychosis, proved to be a valuable treatment for severe depression. Named imipramine (Tofranil), it paved the way for many contemporary antidepressants. Then Hoffman-La Roche, another Swiss company, created chlordiazepoxide (Librium), which doesn’t help psychosis either but does relieve anxiety. It was soon followed by another benzodiazepine, diazepam (Valium), which became the best-selling drug in America for about a decade, beginning in the mid-1960s.

Adding to the excitement over these drugs were a flurry of findings about their effects on neurotransmitters, a class of brain chemicals that transmit signals between nerve cells. By the 1970s it was discovered that chlorpromazine blocks certain actions of a neurotransmitter called dopamine; imipramine augments the actions of several neurotransmitters, including norephinephrine and serotonin; and diazepam amplifies the effects of yet another neurotransmitter, called gamma-aminobutyric acid [GABA]. In each case, the net result is a change in signaling in brain circuits that control emotional aspects of behaviour.

These discoveries spurred a search for other chemicals that would have similar effects on neurotransmission but fewer undesirable side effects than the originals. The search paid off in a stream of new medications that patients perfer. The most famous, fluoxetine [Prozac], was initially identified as a chemical that prolongs neurotransmission by serotonin; it was subsequently shown to be an effective treatment for both severe and moderate depression. Called an SSRI (selective serotonin reuptake inhibitor), it prolongs serotonin’s effects by inhibiting its reuptake by the nerves that release it, which is the normal way that serortonin signaling is terminated. Related drugs, including sertraline (Zoloft), paroxetine (Paxil), fluvoxamine (Luvox), and citalopram (Celexa) soon followed.

So, drugs that affect neurotransmitters are big business. But all is not rosy with this picture: e.g. Seniors and Drugs: Prescribed to death - CBC news, Atypical antipsychotic drugs and risk of ischaemic stroke - British Medical Journal.

Neutrotransmitters

Found a number of fascinating stories of how neurotransmitters were discovered and sketches of what these things do.

Acetylcholine:

One of the first neurotransmitters found was acetylcholine (ACh). Widespread throughout the central nervous system, ACh usually has an excitatory function, but it can also be inhibitory, depending on prevailing conditions at the receptor site. Because ACh acts briskly and is subject to prompt breakdown in the synaptic cleft, it is well suited as the transmitter for motor neurons. Acetylcholine also acts in the autonomic nervous system, where it is responsible for such functions as contracting the pupil of the eye, slowing heartbeat, and stimulating salivation and digestion.

Two poisons that are well known to readers of mystery novels work their deadly effects by blocking the action of ACh. Curare, a plant extract used by South American Indians to treat their arrows for hunting, rapidly causes paralysis; botulin, a toxin produced by bacteria in improperly canned foods, paralyzes the muscles that control breathing and thereby causes suffocation.

In clinical practice, drugs that block the action of ACh are useful in many ways. Short-lived ACh inhibitors are given in eye drops to dilate the pupil for ophthalmic examination. More enduring forms, such as atropine, reduce the secretion of saliva and bronchial fluid, which is helpful for anesthesia; hyoscine, or scopolamine, another related compound, is sometimes used as a sedative but does have the side effect of causing a very dry mouth. Conversely, drugs that inhibit the chemical breakdown of ACh and thus extend its action in the synaptic cleft are at least temporarily effective against myasthenia gravis; this is a crippling disease in which the body's own immune system attacks the receptor sites for ACh on the skeletal muscles. The muscles gradually weaken as they receive fewer synaptic transmissions, but drugs such as eserine can effectively increase the amount of ACh available to the remaining receptor sites.

In the cerebral cortex, ACh is thought to play a role in storing short-term memories. The hippocampus, for example, has dense areas of receptor sites for ACh. (ref.)

Some of the receptors that ACh binds to are also bound to by nicotine.

Serotonin:
a powerful constrictor of blood flow and an inhibitor of some sensations of pain; in recent years, its intriguing variety of effects on our mental life have also come under study. Serotonin is of great importance in regulating sleep; the old folk remedy for sleeplessness, a glass of warm milk before bedtime, may work because of the presence in milk of tryptophan, an amino acid that the brain uses to make serotonin. This transmitter can affect many parts of the brain at once through the long-reaching axons of serotonergic (serotonin-using) neurons, which underlie the transmitter's role in such global phenomena as sleep and mood. The drugs that raise levels of available norepinephrine to alleviate depression also work on serotonin, by the same mechanisms.

(Interestingly, the axons that carry serotonin are not myelinated. Without the electrical insulation afforded by the myelin sheath, impulses travel at less than the lightning speed achieved by, say, signals to the motor neurons, but this seems appropriate to the more global and subjective areas of life regulated by serotonin.) The remarkable effects of lysergic acid diethylamide, or LSD, in even the tiniest quantities, are based on its strong chemical resemblance to serotonin; it is as if a full system of preexisting receptor sites lies ready for the drug's use. One further aspect of this versatile transmitter is that serotonin is featured in biochemical accounts of “sensitization,” the enhanced response to a stimulus as a result of training. Scientists have studied sensitization in extraordinary detail in simple animals such as the marine snail as a model for more complex processes of learning in the human brain (ref.)

Drugs that binds to the serotonin receptors? LSD and Psilocybin

GABA: often acts as a fast synaptic transmission inhibitor. Unlike dopamine or serotonin, which have diverse roles, GABA consistently acts as an “off” signal; the cerebellum, retina, and spinal cord all use this transmitter to inhibit signals, as do many other parts of the brain and nervous system. GABA's inhibitory effect comes about in the following way: the transmitter opens a channel in the membrane through which negatively charged chloride ions can enter the cell. This influx hyperpolarizes the cell and makes it less likely to be excited by incoming stimuli. GABA receptor sites show some tendency to bind barbiturates and the “minor tranquilizers,” the benzodiazepines. Curiously, the presence of GABA in low concentrations enhances the binding of benzodiazepines to receptor sites. This pattern indicates that GABA and the benzodiazepines cannot be competing for exactly the same sites. Instead, an array of recent studies have yielded the view that the GABA receptor site is in fact a multifunctional set of proteins that contain the chloride ion channel and distinct subsites for binding of benzodiazepines, other tranquilizers such as barbiturates, and GABA itself. (ref.)

It appears that both benzodiazepine and barbiturates act by enhancing neural inhibition in the GABA system, although they act at different receptor sites. (ref.)

Glycine:

Glycine is one of the basic amino acids that are used to build protein molecules. Glycine's function as a neurotransmitter is also fairly simple. When released into a synapse, glycine binds to a receptor which makes the post-synaptic membrane more permeable to Cl- ion. This hyperpolarizes the membrane, making it less likely to depolarize. Thus, glycine is an inhibitory neurotransmitter. It is de-activated in the synapse by a simple process of reabsorption by active transport back into the pre-synaptic membrane.

Glycine is a neurotransmitter only in vertebrate animals. The glycine receptor is primarily found in the ventral spinal cord. Strychnine is a glycine antagonist which can bind to the glycine receptor without opening the chloride ion-channel (ie, it inhibits inhibition). (ref.)

Aspartate:

Like glycine, apartate is primarily localized to the ventral spinal cord. Like glycine, aspartate opens an ion-channel and is inactivated by reabsorption into the pre-synaptic membrane. Unlike glycine, however, apartate is an excitatory neurotransmitter, which increases the likelihood of depolarization in the postsynaptic membrane. Aspartate & glycine form an excitatory/inhibitory pair in the ventral spinal cord comparable to the excitatory/inhibitory pair formed by glutamate & GABA in the brain. Interestingly, the two exitatory amino acids -- glutamic acid & aspartic acid -- are the two acidic amino acids found in proteins, insofar as both have two carboxyl groups rather than one. (ref.)

Glutamate: (Yes, the same stuff that's in MSG) - transmitter used to drive fast excitatory synapses. Too much and it becomes 'excitotoxic' and can cause neuron cell death.

Histamine:

associated with wakefulness. In the hypothalamus, histamine is released according to a circadian rhythm. Peak releases of histamine occur during the night together with enhanced locomotion. These observations have led to the idea that brain histamine is implicated in arousal mechanisms and that, in the posterior hypothalamus, histamine released from its neurons contributes to wakefullness and increased locomotion in the night. ... Brain histamine also seems to be involved in memory processes. Central administration of H3 agonists deteriorates, while H3 antagonists improve short-term memory. (ref.)

Epinephrine:

Epinephrine is both a hormone and a neurotransmitter. It's more commonly known as adrenaline. The term "adrenergic" means "epinephrine-using", and is used to describe a class of G-protein coupled receptors that respond to epinephrine. The principal catecholamines are norepinephrine, epinephrine and dopamine. These compounds are formed from phenylalanine and tyrosine. Tyrosine is produced in the liver from phenylalanine through the action of phenylalanine hydroxylase. The tyrosine is then transported to catecholamine-secreting neurons where a series of reactions convert it to dopamine, to norepinephrine and finally to epinephrine.

Catecholamines exhibit peripheral nervous system excitatory and inhibitory effects as well as actions in the CNS such as respiratory stimulation and an increase in psychomotor activity. The excitatory effects are exerted upon smooth muscle cells of the vessels that supply blood to the skin and mucous membranes. Cardiac function is also subject to excitatory effects, which lead to an increase in heart rate and in the force of contraction. Inhibitory effects, by contrast, are exerted upon smooth muscle cells in the wall of the gut, the bronchial tree of the lungs, and the vessels that supply blood to skeletal muscle.

In addition to their effects as neurotransmitters, norepinephrine and epinephrine can influence the rate of metabolism. This influence works both by modulating endocrine function such as insulin secretion and by increasing the rate of glycogenolysis and fatty acid mobilization.

The catecholamines bind to two different classes of receptors termed the a- and b-adrenergic receptors. The catecholamines therefore are also known as adrenergic neurotransmitters; neurons that secrete them are adrenergic neurons. Norepinephrine-secreting neurons are noradrenergic. The adrenergic receptors are classical serpentine receptors that couple to intracellular G-proteins. Some of the norepinephrine released from presynaptic noradrenergic neurons recycled in the presynaptic neuron by a reuptake mechanism.
(ref.)

Norepinephrine:

Also known as noradrenaline, this is widely encountered throughout the nervous system. In the central nervous system, the function of norepinephrine usually complements that of ACh (Acetylcholine); thus norepinephrine acts in the general direction of arousal, and ACh tends toward restorative functions. Norepinephrine dilates the pupil of the eye, strengthens and speeds the heartbeat, and inhibits processes of digestion, all under the heading of what has been called the “fight or flight” response; it also stimulates the adrenal glands to release epinephrine and the liver to release large quantities of glucose, which make more energy available to the muscles for action. Several drugs that work by means of the norepinephrine system are useful in asthma; these are known as the beta-agonists, because they are targeted to a specific group of “beta” receptors in the bronchial muscles, where they relieve constriction.
...
The neurons in the brain that contain norepinephrine cluster in a small region of the brainstem; their axons project to the hypothalamus, the cerebellum, and even the forebrain, a good 10 to 15 centimeters away. Norepinephrine is associated not only with alertness and arousal but also with the dreaming phase of sleep and, by way of the hypothalamus and the limbic system, with the regulation of mood. For instance, a number of studies point to depleted levels of norepinephrine at brain synapses, or a reduced ability of receptors to use it, as a factor in depression. Not that this amounts to a scientific formula that a normal brain minus some amount of norepinephrine equals a depressed mind; such formulas are far too coarse—particularly in an area like the basis of mood, where any number of elements may interact. Moreover, some of the factors that are undoubtedly important for mood are unquantifiable, invisible, and perhaps irreproducible for laboratory study. One point of wide consensus, however, is that depression can be helped by two classes of drugs: one class blocks an enzyme that would normally break down norepinephrine in the synaptic cleft, and the other slows the reuptake of norepinephrine into the presynaptic cell.
...
It is by means of different receptors that norepinephrine, which supplies blood vessels in both skeletal muscle and skin, can cause constriction in the vessels of the skin and dilation in those of muscle. (ref.)

Dopamine:

Dopamine is chemically similar to serotonin and norepinephrine, and it overlaps with them in several biological functions. Formed, like serotonin, from an amino acid, dopamine is actually a precursor to norepinephrine—the same compound except for one different chemical bond—and a wide-ranging neurotransmitter in its own right. In many systems, dopamine acts as an “off” switch: it halts the release of prolactin (which is responsible for the function of the mammary glands), inhibits some cells of the olfactory tract, and also shuts off some of the action of autonomic nerve cells (although this function is not well understood).

Elsewhere in the nervous system, dopamine is important for the control of movement; the degeneration of dopamine-using neurons in a portion of the midbrain leads to Parkinson's disease. A patient with this condition finds it difficult to initiate movement and also to stop, and to manage associated actions such as swinging the arms while walking. A slow tremor of the hands and head, present when the patient is at rest but not during movement, is probably what gave the illness its original name of “the shaking palsy.” Although the progress of the disease cannot be halted, the symptoms of Parkinson's disease can be effectively controlled in most patients by treatment with L-dopa. (This is not the actual transmitter itself but a precursor, a molecule that has the ability to pass through the blood-brain barrier and from which the brain can form dopamine.) Because dopaminergic neurons are also well distributed in the limbic system, we would expect some role for this neurotransmitter in the creation of mood—and, indeed, evidence to this effect is accumulating. Most striking are the signs that a relative increase in dopamine activity in the frontal cortex may provide the biochemical basis for schizophrenia. (ref.)

Cocaine binds to Dopamine receptors.(ref.)

Adenosine: of ATP fame.

Prolonged increased neural activity in the brain's arousal centers triggers the release of adenosine, which in turn slows down neural activity in the arousal center areas. Because the arousal centers control activity throughout the entire brain, the process expands outward and causes neural activity to slow down everywhere in the brain [leading to drowsiness]..."We knew that coffee kept us awake," Dr. Greene said. "Now we know why: Coffee and tea are blocking the link between the prolonged neural activity of waking and increased levels of adenosine in cells, which is why they prevent us from getting drowsy." (ref.)

Nitric oxide: The molecule nitric oxide fills a critical role in diverse tissues of the body, from the lining of blood vessels to the cerebellum, but its identity as a messenger of anything at all was completely unsuspected for a long time. For one thing, the compound—a single atom of nitrogen joined to one atom of oxygen—was very unstable, existing only for a matter of seconds. What could it be doing in the body? It was the well-known effect of nitroglycerin on intense chest pains that first put investigators on the trail of nitric oxide as a messenger molecule. Nitroglycerin works in remarkably small doses to dilate the blood vessels and relieve chest pain. Pharmacologists already knew that nitric oxide was the active ingredient formed by the body from nitroglycerin. But what became clear only in the late 1980s was that nitric oxide was the very substance being sought independently in cardiovascular research as a “relaxing factor” that works in tandem with the neurotransmitter ACh in the lining of blood vessels.

It soon emerged that nitric oxide does not bring about this effect alone; rather it stimulates the production of a second messenger, cyclic GMP (cyclic guanosine monophosphate). As for its origin, nitric oxide is formed by the action of an enzyme from the amino acid arginine; another acid, citrulline, is given off as a by-product. One of the reasons nitric oxide has been so difficult to find in the body is that it is so shortlived (its half-life is five seconds). But the citrulline that is produced at the same time does remain in the system and it can be measured, providing a clue to the evanescent presence of nitric oxide.

At this point in the inquiry, brain researchers began to take an active interest. Solomon Snyder, director of the neuroscience department at Johns Hopkins Medical School, was intrigued by the actions of nitric oxide, and especially by their extraordinary rapidity. He felt sure a system as remarkable as that of nitric oxide could not have developed only for use in blood vessels—it must also be at work somewhere in the brain. Snyder's research team used as their starting point the established fact that when the neurotransmitter glutamate binds to receptor sites, the calcium channels open and a great amount of cyclic GMP is produced. Once the investigators knew what to look for, they could follow two lines of evidence simultaneously: levels of citrulline and levels of cyclic GMP, both of which indicate the action of nitric oxide. Sure enough, stimulating the glutamate receptors in the cerebellum tripled the levels of citrulline and increased the levels of GMP almost tenfold. (Conversely, when the cells were treated with a drug that inhibits the nitric oxide-forming enzyme, no cyclic GMP was produced, even when the glutamate receptors were activated—a check on cause and effect that confirmed the researchers' hunch.)

As another piece of evidence, these great increases in cyclic GMP production all took place within a few seconds. This was a remarkably swift reaction, well within the time frame of some of the more brisk neurotransmitters. It appears that the nitric oxide-forming enzyme is switched on as soon as the calcium channels open, and it begins at once to produce nitric oxide at full speed, with some help from calmodulin, a calcium-binding protein. Thus, nitric oxide is indeed at work in the brain, and it is associated with one of the most important excitatory neurotransmitters — glutamate.

Intriguingly, nitric oxide is neither a transmitter nor a second messenger but truly a different type of messenger between cells. By mapping the areas of the brain where the nitric oxide–forming enzyme tends to concentrate, investigators are beginning to understand more about the action of this substance. Nitric oxide–forming enzyme is found in high concentrations in the cerebellum, which is largely involved in movement, and in the olfactory bulb; it also appears in the pituitary gland (the producer of many hormones), in sections of the eye, and in the intestine (where it may turn out to be the primary agent of muscle relaxation). One of the most exciting of recent results is the finding that certain arteries in the brain contain the enzyme not only in their interior lining but, more unusually, in the neurons that supply the outer layer—the very arteries and nerves recently shown to be involved in migraine headaches. These observations are already being applied in the rapid development of drugs to act at this site in the nitric oxide system, and may soon bring millions of migraine sufferers a new prospect of relief. (ref.)
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Many other neurotransmitters are derived from precursor proteins, the so-called peptide neurotransmitters. As many as 50 different peptides have been shown to exert their effects on neural cell function. Several of these peptide transmitters are derived from the larger protein pre-opiomelanocortin (POMC). Neuropeptides are responsible for mediating sensory and emotional responses including hunger, thirst, sex drive, pleasure and pain. (see Peptide Hormones and Receptors for more info).

Receptors - getting the message across

2006-04-26T21:47:00.000-07:00

From Paul Greengard's Nobel Lecture in 2000:
It is estimated that there are about 100 billion nerve cells in the brain and that on average each of these nerve cells communicates with 1000 other nerve cells. A vigorous debate went on from the 1930s through the 1960s as to whether intercellular communication across the synapses between nerve cells was electrical or chemical in nature. The electrical school of thought held that the nerve impulse or action potential was propagated along the axon to the nerve ending, changed the electrical field across the postsynaptic plasma membrane, and thereby produced a physiological response. The chemical school believed that when the action potential came down the axon to the nerve terminal, it caused the fusion of neuro-transmitter-containing vesicles with the presynaptic plasma membrane, releasing a neurotransmitter, which then diffused across the synaptic cleft and, through activation of a (hypothetical) receptor, produced a physiological response. The chemical school won this debate: over 99% of all synapses in the brain use chemical transmission. (Paul Greengard won the 2000 Nobel Prize in Physiology or Medicine along with Arvid Carlsson and Eric R. Kandel "for their discoveries concerning signal transduction in the nervous system")

Life would be pretty dull if it wasn't for receptors. The senses of smell and vision, hormones, brain functioning - all rely on receptors to make them work. And the details of how they work are being discovered, down to the molecule-by-molecule layout of a single receptor. And the structures disclosed with these techniques are fascinating. No longer regarded as the passive “lock” of a “lock-and-key” mechanism, the receptors appear to work from a few simple elements and to achieve a wide range of effects. Robert Lefkowitz and his colleagues at the Howard Hughes Medical Institute at Duke University have been looking closely at epinephrine and norepinephrine receptor sites [since 1986] Lefkowitz and others succeeded in reading the full genetic sequence of the beta-2 receptor, which allowed them to clone the gene—in effect, to create thousands of copies of the beta-2 receptor in their laboratory. What they learned in the process was astonishing: a single receptor site spans the cell membrane, like a built-in tunnel, no fewer than seven times. The arrangement consists of seven recurring clusters of 20 to 25 amino acids, each crossing the membrane and all held together by loops of amino acids within the cell and just outside the membrane. This pattern appears to hold good for the other kinds of receptors as well. In a comparison of any two receptors, 40 to 50 percent of the sequence is identical—a high degree of conservation and an indication of how effective this structure must be. (From Sandra Ackerman's book Discovering the Brain)

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(A dopamine receptor is on the left, and a serotonin receptor is on the right

From Evolution of Signal Transduction: Animals are especially fond of these receptors. The genome of the nematode worm is now done and it contains 1049 G-protein coupled receptors. These may be chemosensory receptors.

From Richard Axel's 2004 Nobel Lecture: The completed sequence of both the [mouse] and human genome ultimately identified 1300 odorant receptors in the mouse and 500 in humans. If mice possess 20,000 genes, then as much as 5% of the genome, one in 20 genes encodes the odorant receptors. And all of these receptors that the sense of smell relies on are based on the same serpentine arrangement where the receptor protein passes through the membrane 7 times. The 3 "extra-cellular" loops of the protein that are outside of the cell membrane have a specific shape and composition that binds with 'ligands', i.e. molecules that can reversibly bind with the receptor protein (usually with some molecular surface features which 'fit' well with the shape of the receptor protein).

G protein-coupled receptor (GPCR)
For the receptors we've been discussing so far, there is a "G Protein" molecule inside of the cell membrane that gets activated when this change in shape occurs. It's called a "G Protein" because it is a glycoprotein that is anchored on the cytoplasmic cell membrane that binds the guanine nucleotide (one of the bases that is used to build DNA). When combined with the sugar ribose... guanine forms a derivative called guanosine (a nucleoside), which in turn can be phosphorylated with from one to three phosphoric acid groups, yielding the three nucleotides GMP (guanosine monophosphate), GDP (guanosine diphosphate), and GTP (guanosine triphosphate).(ref.).
Almost all members of this superfamily of proteins act as molecular switch, which is on when GTP is bound and off when GDP is bound. Binding is specific for the guanine base[ and is 6 orders of magnitude higher for GDP and GTP than it is for GMP and other nucleotide bases]. (ref.)

From Indiana State U.:
The link between neurotransmitters and intracellular signaling is carried out by association either with G-proteins (small GTP-binding and hydrolyzing proteins) or with protein kinases, or by the receptor itself in the form of a ligand-gated ion channel (for example, the acetylcholine receptor). One additional characteristic of neurotransmitter receptors is that they are subject to ligand-induced desensitization: That is, they can become unresponsive upon prolonged exposure to their neurotransmitter.

Bruce Jenks at Radboud University Nijmegen has put together some cool flash animations. From his site:
The G proteins associated with receptor transduction are the so-called "trimeric" G proteins because they are composed of three subunits, alpha, beta and gamma. (The trimeric designation distinguishes the receptor-associated G proteins from smaller intracellular "monomeric" G proteins that are involved in vesicular traffic and other processes within the cell.) When the neurotransmitter[or hormone or odour or whatever] binds with the receptor, it exerts molecular-level forces on the protein which cause the shape of segments inside of the cell membrane to change. Intracellular loops of the receptors are responsible for the activation of the G proteins. After activating a G protein the ligand-receptor complex remains active and can activate more G proteins. In this sense, one can think of the activated ligand-receptor complex as an enzyme.

Molecular tinkering of G protein-coupled receptors: an evolutionary success
GPCRs have a central common core made of seven transmembrane helices (TM-I to -VII) connected by three intracellular (i1, i2, i3) and three extracellular (e1, e2, e3) loops. The diversity of messages which activate those receptors is an illustration of their evolutionary success. The diagrams at left show the classification and diversity of GPCRs. Figure A: Three main families (1, 2 and 3) can be easily recognized when comparing their amino-acid sequences. Receptors from different families share no sequence similarity, suggesting that we are in the presence of a remarkable example of molecular convergence. Family 1 contains most GPCRs including receptors for odorants. Group 1a contains GPCRs for small ligands including rhodopsin and β-adrenergic receptors. The binding site is localized within the seven TMs. Group 1b contains receptors for peptides whose binding site includes the N-terminal, the extracellular loops and the superior parts of TMs. Group 1c contains GPCRs for glycoprotein hormones. It is characterized by a large extracellular domain and a binding site which is mostly extracellular but at least with contact with extracellular loops e1 and e3. Family 2 GPCRs have a similar morphology to group Ic GPCRs, but they do not share any sequence homology. Their ligands include high molecular weight hormones such as glucagon, secretine, VIP-PACAP and the Black widow spider toxin, α-latrotoxin. Family 3 contains mGluRs and the Ca2+ sensing receptors. Last year, however, GABA_B receptors and a group of putative pheromone receptors coupled to the G protein G_o (termed VR_s and G_o-VN) became new members of this family. Figure B: Family 4 comprises pheromone receptors (VNs) associated with Gi. Family 5 includes the 'frizzled' and the 'smoothened' (Smo) receptors involved in embryonic development and in particular in cell polarity and segmentation.(refs.)
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From the conclusion of Alfred G. Gilman's 1994 Nobel lecture:
Why G Proteins?
One might well ask why G proteins are included in signaling pathways and why the systems are so complex structurally. Transmembrane signaling is clearly accomplished with simpler [...] molecular assemblages, such as tyrosine kinases, ligand-gated ion channels, and receptor guanylyl cyclases. I believe there are several reasons for the evolution of complex signaling systems. At a relatively simple level, the existence of these molecular switches and timers permits enormous amplification in the signaling process. A single agonist-receptor complex can catalyze the activation of many G proteins during the time that a single G protein a subunit remains, active; delayed deactivation of the alpha subunit permits further amplification at the level of catalytic effector molecules. There is also the possibility of substantial regulatory complexity, with opportunities to modulate both the quantitative and qualitative aspects of signaling by alterations in rates of synthesis and degradation of many gene products, as well as more acute regulation by covalent modification of these molecules. Most importantly, perhaps, the tripartite nature of these signaling systems permits enormous diversity of outputs. G protein-regulated signaling pathways are characterized by both convergence and divergence at each step. Many different kinds of receptors can converge to activate a single type of G protein, while a single type of receptor can interact with more than one species of G protein to initiate several events. Similarly, different G proteins may converge on a single effector to alter its activity, either additively, synergistically, or antagonistically, while a single G protein may also interact with more than one effector. G proteins can also exert effects via either their alpha or beta gamma subunits. The complexity of the cellular switchboard thus appears sufficiently vast to permit each cell to design a highly customized signaling repertoire by expression of a relatively modest number of modular components.

Second messengers
From Brainfacts, from the Society for Neuroscience: Substances that trigger biochemical communication within cells, after the action of neurotransmitters at their receptors, are called second messengers; these intracellular effects may be responsible for long-term changes in the nervous system. They convey the chemical message of a neurotransmitter (the first messenger) from the cell membrane to the cell’s internal biochemical machinery. Second messenger effects may endure for a few milliseconds to as long as many minutes.

An example of the initial step in the activation of a second messenger system involves adenosine triphosphate (ATP), the chemical source of energy in cells. ATP is present throughout the cell. For example, when norepinephrine binds to its receptors on the surface of the neuron, the activated receptor binds G proteins on the inside of the membrane. The activated G protein causes the enzyme adenylyl cyclase to convert ATP to cyclic adenosine monophosphate (cAMP). [Shockwave animation from Signal Transduction Cascades] The second messenger, cAMP, exerts a variety of influences on the cell, ranging from changes in the function of ion channels in the membrane to changes in the expression of genes in the nucleus, rather than acting as a messenger between one neuron and another. cAMP is called a second messenger because it acts after the first messenger, the transmitter chemical, has crossed the synaptic space and attached itself to a receptor. Second messengers also are thought to play a role in the manufacture and release of neurotransmitters, intracellular movements, carbohydrate metabolism in the cerebrum. Direct effects of these substances on the genetic material of cells may lead to long-term alterations of behavior.

OK, so when a ligand binds to a receptor it effectively turns on an enzyme reaction or an ion channel, which can cause quite significant changes of functionality within the cell. But a switch that can only be turned on once and can never be turned off is kinda useless. How do the receptors get 'turned off' once they've been activated? i.e. How do the ligands get removed from the receptors?

One of the ways this happens is with the help of clathrin (yes, our friend the super cool cellular transport molecule). In addition to having a binding site for a ligand molecule, receptors also have a binding site for a protein called adaptin. Once adaptin has bonded with the receptor, it tows it towards a clathrin coated pit, which is tethered to the cell membrane via the cell's cytoskeleton (ref.).

Once enough receptors have accumulated in the pit, the pit pinches off to form an enclosed bubble called an endosome which carries the receptors and their attached ligand molecules into the cell in a process called endocytosis. The pH within the endosome drops to 5.9-6.0, which is sometimes enough to strip the ligand from the receptor. The receptors can then be recyled, by moving back to the membrane.

Those endosomes carrying receptors with ligands that get past this stage are called 'late endosomes'. Their pH continues to drop to 5.0 to 6.0 range, and they can be given digestive enzymes that further help in removing the ligands from the receptors. If the ligand survives this stage, the endosome fuses with a lysosome within the cell, which drops the pH to the 5.0 to 5.5 range and is capable of breaking apart both the ligand and the receptor itself. Check out this cool website from the University of Texas for more information on this fascinating process.

Getting rid of the ligand by itself is not sufficient to turn off the process associated with the receptor - if there are more ligands (e.g. neurotransmitters or hormones) hanging around the cell membrane, they will simply bind with the recycled receptors and the process will continue. To truly turn off the signaling, the ligands have to be removed from the vicinity of the receptors. There are at least 4 ways that this can happen:

Diffusion: e.g. the ionic concentration in the extra-cellular fluid that the ligand is in can exert pressure on the molecule, causing it move to an area with a weaker ionic concentration.

Enzymatic degradation (deactivation): a specific enzyme changes the structure of the neurotransmitter so it is not recognized by the receptor. For example, acetylcholinesterase is the enzyme that breaks acetylcholine into choline and acetate.

Glial cells: astrocytes remove neurotransmitters from the synaptic cleft.

Reuptake: the whole neurotransmitter molecule is taken back into the axon terminal that released it. This is a common way the action of norepinephrine, dopamine and serotonin is stopped...these neurotransmitters are removed from the synaptic cleft so they cannot bind to receptors.

One of the major areas of pharmaceutical research is identifying 'uptake inhibitors' which can interfere with the uptake mechanism and prolong the length of time that the receptor is activated.
(ref.)

Within the brain, there are two broad categories of receptors - those that act slowly, like the GPCR receptors that trigger second messengers discussed earlier, and those that act quickly by controlling ion channels, for example.
Back to Paul Greengard's Nobel Lecture:We know today that there are two categories of chemical transmission between nerve cells, which are referred to as fast and slow synaptic transmission. About half of the fast synaptic transmissions in the brain are excitatory, and most of these utilize glutamate as their neurotransmitter [which causes a conformation of the receptor it binds to, which opens up the ion channel and allows ions to rush into the cell, causing depolarization]. The other half of the fast synaptic transmissions are inhibitory and most use GABA [Gamma-AminoButyric Acid] as their neurotransmitter.

Gary G. Matthews has created some cool animations that show how fast-acting neurotransmitters act directly as ligands which open ion channels for both excitatory and inhibitory synaptic transmissions, and slow-acting neurotransmitters act indirectly through G-protein coupled receptors.

Wiki's entry on GABA:In vertebrates, GABA acts at inhibitory synapses in the central nervous system. GABA acts by binding to specific receptors in the plasma membrane of both pre- and postsynaptic cells. This binding causes the opening of ion channels to allow either the flow of negatively-charged chloride ions into or positively-charged potassium ions out of the cell. This will typically result in a negative change in the transmembrane potential.

Three general classes of GABA receptor are known. These include GABA_A and GABA_C ionotropic receptors, which are ion channels themselves, and GABA_B metabotropic receptors, which are G protein-coupled receptors that open ion channels via intermediaries

Paul Greengard: Slow synaptic transmission, which occurs over periods of 10s of milliseconds, is enormously more complex than fast synaptic transmission. ... It is very likely that all of the biogenic amines, and all of the peptide neurotransmitters, produce their effects on the target cells through slow synaptic transmission. And even the fast acting neurotransmitters, including glutamate and GABA, produce many of their effects through slow synaptic transmission pathways. In fact, Liu et. al (Nature 403: 274-280) have shown that receptors can interact with each other in the cell membrane, even slow GPCR receptors like dopamine receptors and fast ion channel receptors like the GABA receptor. (check out Bruce Jenk's GPCR-ion channel interactions presentation). These type of interactions increase the range of responses a cell can produce in react to one or more neurotransmitters.

And it's important to note that for each neurotransmitter there can be many different receptors, each capable of producing different effects in the cell when activated. In fact, the same neurotransmitter is frequently used in different areas for completely different purposes. This is one reason that therapies that involve artificially introducing neurotransmitters as a drug can have devastating side-effects.

Another surprising thing is that just because a neurotransmitter gets released at one synapse that an axon terminates on doesn't necessarily mean that all of that axon's synapses will release that neurotransmitter. It's amazing how subtle and complex the brain really is.

More...

HybridMedicalAnimation's extremely cool receptor and co-receptor agonist animation.

Linda Buck's excellent 2004 Nobel lecture Unraveling the Sense of Smell

Bruce Jenks website at Radboud University Nijmegen: Cell Signaling

Receptor Mediated Endocytosis - provides a lot of good info on how receptors are recycled within the cell

Orientations of Proteins in Membranes (OPM) database is quite mindblowing. 3D rotational views of proteins in membranes. Wow.

Evolution of Signal Transduction discusses other types of receptors not covered here, including nuclear receptors that drive gene transcription.

Thermodynamic properties and heterogeneity of membrane assemblies. - "It is assumed usually that the lipid membrane acts as an anchor for the proteins and has no independent function. However, membranes contain hundreds of different lipids which are different with respect to their physical properties (for example charge and size)."

Martin Rodbell's 1994 Nobel Lecture: SIGNAL TRANSDUCTION: EVOLUTION OF AN IDEA - points out interesting similarities between G-Proteins and Cytoskeletal proteins.

Clathrin - the super cool cellular transport machine

2006-03-06T12:34:00.000-08:00

From the University of Hamburg's website: Clathrin and Coated Vesicles:
Clathrin is a protein with an extraordinary structure. It is a trimer with three leg-like subunits. Its extraordinary structure enables the protein to polymerize in a two-dimensional network consisting of numerous hexagons. Strictly speaking [the aggregate forms not a plane but] a bent surface with a convex and a concave side. It is an open question whether the tendency to bend has intramolecular or intermolecular causes. Especially important is the fact that such networks fit with their concave side tightly to membranes, for example to the inner surface of the plasmalemma. The growing network provides the mechanical force to pull the membrane into a bud. This bud is finally pinched off: a clathrin-coated vesicle has been formed.

Coated vesicles are known to exist in a range of plant and animal cells (E. H. NEWCOMB, 1980). They bring extracellular substances into the cell, a process called endocytosis. Within the cell, the coated vesicles have the chance to fuse with other vesicles, for example with lysosomes. Their content is then digested by the lysosomal enzymes, the clathrin coat is dismantled and available for a new cycle.

The picture at the top of this blog entry shows the structure of clathrin. A: a single molecular complex. B: aggregation of the clathrin molecules at the surface of a coated vesicle. The hexagons are easily detected in the electron microscope:

Electron microscope view of a clathrin coated pit, showing hexagonal grid structure that can fold up geodesically

From SynapticSystems: Clathrin consists of heavy chains and light chains that co-assemble to triskelions. The light chains are differentially spliced, with neurons expressing a special variant that is not detectable elsewhere. The neuron-specific light chains are enriched in synaptic nerve terminals where they participate in synaptic vesicle endocytosis.

From Harvard University's website:Under the Hood of a Cellular Transport Machine
Clathrin-coated vesicles are constantly assembling and disassembling to perform their task of transporting proteins from the outside of the cell inside. They are responsible for importing LDL cholesterol, and they play a role in breast cancer through internalization of a key receptor. During disease progression of HIV infection, clathrin-coated vesicles are subverted by a viral protein to cause down-regulation of the viral receptor CD4 in an important but not fully understood step. These molecules, and a wide range of others, are selectively trapped in the clathrin-coated vesicle for import into the cell. The new insights into how the vesicle forms help build a picture of the overall process and suggest possible targets for future therapeutic intervention.

One mystery of clathrin vesicles is how the outer cage of clathrin assembles so rapidly. Vesicles are incessantly assembled and disassembled at an incredible scale. In the brain, where neurotransmitters are constantly released into synapses, the membrane used to export the neurotransmitters is constantly being dragged back in by clathrin-coated vesicles. "The equivalent of the entire brain, or a football field of membrane, is turned over every hour," says Tomas Kirchausen, associate professor of cell biology at the Center for Blood Research and Harvard Medical School and senior author on the article last year describing clathrin's atomic structure.

The new work allows Kirchhausen and colleagues to propose that clathrin molecules add to the growing cage lattice by hooking into spaces in the existing structure, then rapidly rotating into a locked position. The process is reminiscent of images of alien space ships locking into the mother vessel.

The new insights come from combining an overall view of a barrel-shaped clathrin lattice, obtained using cryo-electron microscopy by Barbara Pearse and colleagues at the MRC Laboratory for Molecular Biology in England, with the much more detailed view of a portion of the protein derived from X-ray crystallography by Tomas Kirchhausen, Stephen Harrison, and colleagues at Harvard Medical School, the Center for Blood Research, Children's Hospital and the Howard Hughes Medical Institute, and Andrea Musacchio, now at the European Institute of Oncology in Milan, Italy.

Click here to see a movie of how clathrin molecules form a geodesic sphere.

From a NewScientist article on work done by Ehler's Lab:
'Doorways' discovered in living brain cells
Brain cell membranes contain fixed "doorways" that control the entry of molecules into the cell, new research shows. The realisation represents a fundamental shift in the understanding of how neurons work.

"We have found that the nerve cell is in a way like a room with only certain entry points, or doorways. Before, it had been thought that substances could move through the cell membrane at any point," says lead researcher Michael Ehlers at Duke University, North Carolina.

To enter a brain cell, molecules such as receptors or pathogens must first be transported to the doorway sites. Understanding this process, and how to control it, could one day lead to an entirely new class of treatments for depression, epilepsy, addiction and other neurological disorders, Ehlers says.

The researchers also found that the number and location of the entry points becomes further stabilised with age. This might partly explain why brain regions become less "plastic" - less able to change function - as they become older, he says.
...

The brain establishes memory pathways, for example, by adjusting the strength of connections between neurons. This involves the precise control of the number of receptors for neurotransmitters (the brain's chemical messengers) on the receiving surface of a cell.

Neuroscientists knew brain cells could reduce the strength of a connection by reducing the number of surface neurotransmitter receptors. They do this by allowing the receptors leave the membrane and enter the cell.

They also knew that receptors, and other molecules, enter a cell via pits coated with a molecule called clathrin. But until now they thought these clathrin pits could form at any point on the membrane.

Ehlers Lab's website is excellent: e.g. Protein Trafficking machinery in Dendritic Spines and Clathrin Dynamics and the Endocytic Zone
All neuronal functions including synaptogenesis, synaptic transmission and synaptic plasticity require regulation of the surface expression of membrane proteins such as neurotransmitter receptors. One mechanism neurons use to accomplish this task is endocytosis, the process by which surface proteins are taken into the cell via a membrane-enclosed vesicle. For example, recent studies have shown that glutamate receptors, which mediate fast excitatory synaptic transmission, undergo an activity-dependent endocytosis, thus controlling synaptic strength. In addition, recent research in the Ehlers' lab has discovered a specialized membrane domain in dendritic spines termed the 'endocytic zone', where clathrin-mediated endocytosis occurs. In this light, my research is aimed at characterizing the functions of endocytic machinery proteins in dendrites and identifying their roles on endocytosis of glutamate receptors.
...
A major question in synaptic receptor trafficking has been whether spines contain the machinery necessary for insertion and endocytosis of neurotransmitter receptors. Here, we show that clathrin coats form in most spines in cultured neurons. Clathrin coats in spines mediate endocytosis, in this case of Tf receptors. This demonstrates a remarkable self-sufficiency for spine membrane trafficking, and also indicates that the cargo-selectivity of endocytic coats in spines is low. Our first clue that the endocytic machinery in spines was distinct from the synapse itself came from the relatively low rates of colocalization of synaptic markers such as the scaffold protein shank, with clathrin-GFP puncta. The segregation of the endocytic zone from the postsynaptic density (as marked by PSD-95 expression) was striking. Despite an amazing diversity of PSD size and shape, the overwhelming majority of PSDs are closely associated with a clathrin coat. See our review article for more information regarding the importance of this organization in psychiatric disease.

Another protein that transports molecules across membranes in a similar way is caveolin. HybridAnimation's beautiful animation shows 'the formation of specialized sac-like structures called caveolae that transport cargo through the endothelial wall. (see picture at right). More info on caveolin proteins is available here

Proposed functions of caveolae and the caveolins (adapted from (Razani and Lisanti, 2001))

A) Certain molecules have been shown to be predominantly endocytosed via caveolae and not clathrin-coated vesicles.
B) shows how both clathrin and caveolin are involved in carrying lipoprotein molecules through the cell membrane to and from the Golgi apparatus. (Check out John Kyrk's Golgi apparatus flash animation for a cool look at vesicles forming and carrying molecules within the cell.
C) Caveolae are now thought to act as signalosomes, or entities in which signal transduction events can take place efficiently. A higher level of regulatory complexity is provided by the caveolins where signaling molecules can be bound until extracellular ligands relieve them of inhibition. Here, the dynamic regulation of a receptor tyrosine kinase (e.g. EGF receptor) and a lipid-modified kinase (e.g. the src-tyrosine kinase) in caveolae are shown.

From Time Resolved Microfluorimetry: One of the most important membrane transport mechanisms is receptor mediated endocytosis (RME), responsible for triggering and regulating many fundamental cell processes, such as growth, nutrition, secretion, transfer of immunity to the foetus, motility, and cell adhesion. At the heart of RME is the receptor, a protein that picks up and transports specific molecules and particles (ligands) across the cell (see figure below). The surface of each cell is covered with transmembrane receptors. The ‘docking’ of the ligand to the receptor triggers a response in the cell which will be uniquely determined by the nature of the receptor/ligand complex and the type of cell. Following ligand binding, the receptor/ligand complexes enter the cell as coated vesicles (endosomes), which are formed when pits in the membrane pinch off. This internalisation can provide a signal for amplification or attenuation of a specific cellular response. Unfortunately, many harmful toxins and viruses can also be transported by this mechanism. Viruses for example have evolved to exploit RME by adapting their coat proteins so that they will bind strongly to certain receptors and be transported into the cell.

More...
There's a fascinating article in Nature called Spatial control of coated-pit dynamics in living cells that dives into how clathrin coated pits are tethered to the cell membrane and how the cell manages them in both time and space.

Nanobiology Notes

2006-02-19T20:39:00.000-08:00

The series of notes on molecular biology I posted initially to this blog have been moved to a new blog:
Nanobiology Notes:

Just add water...
Fun with Molecular Origami
Chromosomes: Good things come in very small packages
Protein formation: Codones, Histones and Ribosomes
Life and Ligands
Ion Channels: gates in the cell wall
Enzymes: Come together, right now, over me.
ATP: Power to the people, right on!

21st Century Lego: Synthetic Biology and Molecular Engineering

2005-12-14T20:15:00.000-08:00

As long as I can remember, I've always enjoyed designing and building stuff. I have clear memories of building things with tinkertoy when I was around 3 years old, and as I grew up I made the usual progression through Lego, mechano, balsa wood models, electronics, software, ... The stuff you can build is limited only by the properties of the building materials, your skill level and knowledge, and your imagination. Well, wouldn't it be cool if you could build stuff out of molecules? If, through synthetic biology, you could craft some DNA to create the necessary infrastructure within a cell to create a tiny manufacturing plant for, say, carbon nanotubes?

First thing to do when some far out idea like this pops into your head is to see if someone else has thought of it too (which is almost always the case).
c.f.: http://ej.iop.org/links/q30/2N8tYInWNdqdYgCQ2+AZJg/nano5_1_R01.pdf

As we become more adept at modifying proteins not just for binding but for catalysis, the nanotechnologist can begin to glimpse some rather dizzying prospects. Can one design an enzyme that constructs carbon nanotubes [39], perhaps even with a specified diameter and chirality (and hence electronic structure)? Could such a molecule then be fitted with a recognition tag that will ensure it does its job of construction only at a particular location in a semiconductor landscape?

Natural proteins and protein-based assemblies have shown considerable potential for nanotechnological applications. The light-activated proton pump bacteriorhodopsin, a membrane protein that regulates the pH of some bacterial cells, is perhaps the prototype, having been used over 10 years ago as a material for optical molecular data storage [40].

More recently, Meier et al [41] have shown that this and other membrane proteins will retain their structure and function when immobilized in thin, robust films of
crosslinked copolymers with a hydrophilic–hydrophobic–hydrophilic sandwich structure, mimicking the environment of lipid membranes. Ho et al [42] used bacteriorhodopsin immobilized in such a polymer membrane to actively pump protons against a pH gradient and thereby to reduce hydrogen ion leakage across the proton exchange membrane of a fuel cell.
...
More ambitiously, can we imagine designing a cell that will build a genuine photovoltaic cell based on the chloroplast, or a versatile and programmable polymer synthesis factory based on the ribosome?
...
It is not at all hard to envisage bacteria or viruses acting as sensor devices that detect and signal (by fluorescence, say) traces of certain substances in their environment. More startling, perhaps, are possibilities such as programming cells to reproduce the algorithms of cellular automata—an ironic reversal of the metaphor—so that they interact with their neighbours in tightly prescribed ways, allowing them to develop spontaneous patterns, collective and multicelled behaviour, and even forms of computing

NASA Ames Research Lab
from http://ameslib.arc.nasa.gov/randt/2000/science/space5.html :

Ames is focusing on a major component of all cells (proteins) that are capable of self-assembling into highly ordered structures. A protein known as HSP60, which spontaneously forms nano-scale ring structures that can be induced to form chains or filaments is currently being studied.

ring structures (fig. 1a, end view; 1b, side view), chains (fig. 1c),filaments (fig. 1d)

With thermostable HSP60s, highly efficient methods have been developed for purifying large quantities of these proteins; their composition and structure-forming capabilities are being currently modified by using the "tools" of molecular biology. For example, if a small fragment of the HSP60 protein is removed, protein rings are produced that do not form chains or filaments, but continue to form rings that spontaneously assemble into highly ordered hexagonally packed arrays. If these proteins are modified to bind metal atoms, they can be used as a template to create an ordered pattern of metal on a surface with nanometer spacing. Ultimately the hope is to use such ordered arrays of metal to manufacture nano-scale electronic devices. Similarly, metal binding to proteins that form filaments may be used to create self-assembling nano-scale wires, which may someday be used to produce self-assembling circuits.

Modified proteins form hexagonally packed rings (left) or metal-containing protein filaments (right)

MIT's Biobricks

from http://parts.mit.edu/ : A registry of 'standard biological parts' aka bio-bricks:

from http://www.eetimes.com/news/latest/showArticle.jhtml?articleID=21800320

There are currently about 300 BioBricks, and another 800 parts have been built by combining those into composite BioBricks. Knight and his collaborators presented results on a next generation of the system called BioBricks++.

Just as object-oriented programming constructs allowed programmers to quickly combine previous software modules into more complex systems, the BioBricks++ system has standard interfaces for all DNA segments that can be combined in any sequence using commercially available enzymes.

Rettberg is working on an online data book, and is initiating a standards process so that anyone can build BioBricks and add them to the catalog. He envisions an assembly service with measurement and quality control leading to the evolution of "open source biology". Rettberg is also organizing a summer design contest sponsored by the National Science Foundation and the Defense Advanced Research Projects Agency, where teams of graduate and undergraduate students will genetically engineer a Finite State Machine

more:
http://www.eetimes.com/news/latest/showArticle.jhtml?articleID=21700333
http://icampus.mit.edu/projects/iGem-EETimes-MITBioBricks.pdf

Live long and prosper...

2005-12-14T06:35:00.000-08:00

Genetically Engineered Mice Defy Aging Process
Scientists have prolonged the lives of laboratory mice by 20 percent using a technique that boosts the natural antioxidants of the body.

Scientists Find Anti-Aging Gene in Mice
The discovery was triggered by a study Kuro-o and his colleagues published in 1997. That study identified a gene in mice that, when damaged, caused the animals to experience all the hallmarks of aging in humans -- hardening of the arteries, thinning bones, withered skin, weak lungs -- and to die prematurely. They dubbed the gene Klotho, for the Greek goddess who spins the thread of life.

Suspecting the gene may play a role in regulating life span, Kuro-o and his colleagues genetically engineered mice with overactive Klotho genes. In the latest experiments, they found that these animals lived an average of 20 to 30 percent longer than normal -- 2.4 to 2.6 years vs. a normal life span of about two years -- without any signs of ill effects, according to the new report.
...
The researchers then identified a small protein component, called a peptide, that the gene produces and found it circulating in the animals' blood at double the normal level.

After isolating and purifying the substance and reproducing it through genetic engineering techniques, the researchers injected the substance into normal mice. Tests on those animals, combined with experiments involving cells in the laboratory, indicate that the substance modulates [the insulin/insulin-like growth factor-1 signaling] pathway involved in an array of basic metabolic functions that has become the focus of aging research in recent years.

Mechanisms of Aging

The "mitochondrial theory of aging" postulates that damage to Mitochondrial DNA (mtDNA) and organelles by free radicals leads to loss of mitochondrial function and loss of cellular energy (with loss of cellular function). Mutations in mtDNA occur at 16 times the rate seen in nuclear DNA. Unlike nuclear DNA, mtDNA has no protective histone proteins. And DNA repair is less efficient in mitochondria than in the nucleus. These factors account for the more rapid aging seen with Complex I & III as compared to Complex II & IV. Aging mitochondria become enlarged and, if they can be engulfed by lysosomes, are resistant to degredation and contribute to lipofuscin formation [EUROPEAN JOURNAL OF BIOCHEMISTRY; Brunk,UT; 269(8):1996-2002 (2002)].

A comparison of 7 non-primate mammals (mouse, hamster, rat, guinea-pig, rabbit, pig and cow) showed that the rate of mitochondrial superoxide and hydrogen peroxide production in heart & kidney were inversely correlated with maximum life span [FREE RADICAL BIOLOGY & MEDICINE 15:621-627 (1993)]. A similar study of 8 non-primate mammals showed a direct correlation between maximum lifespan and oxidative damage to mtDNA in heart & brain. There was a 4-fold difference in levels of oxidative damage and a 13-fold difference in longevity, supportive of the idea that mtDNA oxidative damage is but one of several causes of aging [THE FASEB JOURNAL; Barja,G; 14(2):312-318 (2000)].

A comparison of the heart mitochondria in rats (4-year lifespan) and pigeons (35-year lifespan) showed that pigeon mitochondria leak fewer free-radicals than rat mitochondria, despite the fact that both animals have similar metabolic rate and cardiac output. Pigeon heart mitochondria (Complexes I & III) showed a 4.6% free radical leak compared to a 16% free radical leak in rat heart mitochondria [MECHANISMS OF AGING AND DEVELOPMENT 98:95-111 (1997)]. Hummingbirds use thousands of calories in a day (more than most humans) and have relatively long lifespans (the broad-tailed hummingbird Selasphorus platycerus has a maximum lifespan in excess of 8 years). Birds have less unsaturation (oxidizability) in their mitochondrial membranes and have higher levels of small-molecule antioxidants, such as ascorbate & uric acid. Even for mammals there is a direct relationship between mitochondrial membrane saturation and lifespan [JOURNAL OF LIPID RESEARCH 39:1989-1994 (1998)].

Free-radicals from mitochondria result in damage to cellular protein, lipids and DNA throughout the cell. This damage has been implicated as a cause of aging. If the fatty acids entering the mitochondria for energy-yielding oxidation have been peroxidized in the blood, this places an additional burden on antioxidant defenses. The greatest damage occurs in the mitochondria themselves, including damage to the respiratory chain protein complexes (leading to higher levels of superoxide production), damage to the mitochondrial membrane (leading to membrane leakage of calcium ions and other substances) and damage to mitochondrial DNA (leading to further damage to mitochondrial protein complexes). An experiment in yeast that improved the accuracy of mitochondrial protein synthesis demonstrated a 27% longer mean life span [JOURNAL OF GERONTOLOGY 57A(1):B29-B36 (2002)].

The first test-tube baby was nick-named Pandora's baby. I have a hunch that the first application of genetic engineering to humans that will make the concept compelling will be to offer parents the option of longer life for their child at the in vitro fertilization stage.

Here comes the bio-electronics revolution...

2005-12-12T12:36:00.000-08:00

Adam Heller at the University of Texas at Austin has developed an implantable electrode module, the first component of a biofuel cell in which glucose is electro-oxidized at the anode and oxygen is electroreduced at the cathode at neutral pH. The volumetric power density of the cell, including the liquid passing through it, will be around 1mW/cm at the glucose and oxygen concentraions of arterial blood.

The secret to the fuel cell's size and performance is the use of microfibers rather than flat electrodes and the enzyme-based electroactive coatings. This electrode design avoids glucose oxidation at the cathode and O2 reduction at the anode, Heller points out, eliminating the need for an electrode-separating membrane, which is difficult to produce and enclose when small.

The anode coating is glucose oxidase covalently bound to a reducing-potential copolymer that has osmium complexes tethered to its backbone. The cathode coating is similar but contains the enzyme laccase and an oxidizing-potential copolymer. In the coatings, a network of osmium redox centers electrically "wires" the reaction centers of the enzymes to the carbon fibers.

The enabling breakthrough, Heller says, was the group's earlier development of the "wired" laccase cathode that facilitates the four-electron reduction of O2 to water near neutral pH (pH 5) at body temperature (37 °C) [J. Am. Chem. Soc., 123, 5802 (2001)]. Reduction of O2 to water under these conditions has been one of the long-standing problems in electrochemistry, Heller notes. Until now, only noble metal electrodes at pH 0 or carbon electrodes at pH 14 were used for the reduction.
(article)

CMOS, biochips to share International Solid-State Circuits Conference bill
11/28/2005 (EETimes)

In bioelectronics, one remarkable example is a flip-chip combination of a mixed-signal ASIC and an electrode array intended to be implanted in the inner ears of guinea pigs. The ASIC communicates with the outside world and draws power via a wireless interface. It relays signals to the electrode chip, which directly stimulates the animal's auditory nerve. A denser device could potentially be used for hearing-impaired humans. Two papers each will describe DNA recognition chips, retinal-implant ICs and biosignal acquisition chips

Real-world implants are arriving
09/12/2005 (EETimes)
Electronics engineers, surgeons and medical researchers are tackling a variety of difficult problems in their quest to blend electronics technology with physiology: how to connect to nerve nets and talk to them, how to power implanted electronic components, how to devise low-power neuromorphic circuit design methodologies and how to build sensors, such as artificial retinas, based on them.

During the past 10 years, Cyberkinetics Neurotechnology Systems (Foxborough, Mass.) has built a business out of supplying implantable electrode systems to medical researchers. The company is now planning a series of products for use in clinics. In development is the BrainGate Neural Interface System, designed to give physically disabled people the ability to control computers, robotic arms or environmental controls in a house.

The direction this capability is taking can be seen at Miguel Nicolelis' lab at the Center for Neuroengineering at Duke University (Durham, N.C.). Nicolelis and his colleagues have developed a neurochip with 128 leads that can be implanted in the brain. They are using the system, along with supporting electronics, to investigate how cognitive events are translated into the movement of limbs.

In the near term, electrodes that can be implanted and communicate with the nervous system are being used in products marketed by Medtronic Inc. (Minneapolis). Applications include controlling Parkinson's tremors, alleviating pain and controlling heart rhythms to avoid attacks.

Helping to restore sight and hearing are also high on the list of therapeutic systems that might eventually be implanted in the body. Loss of hearing has been easier to tackle (see main story); an implantable retina is much more problematic. The eye and optic nerves are complex systems and involve sophisticated mechanical feedback. Simply getting a component that can restore even rudimentary vision has been challenging.

The first success in this direction was achieved three years ago by Mark Humayun's group at the Doheny Retina Institute at the University of Southern California. Eye surgeons were able to implant a 4 x 5-mm chip with 16 electrodes that partially restored vision in a blind patient. The procedure has been successfully repeated on five more patients. Humayun's project is part of the cooperative, multipartner Artificial Retina Project, which will extend the work to more-sophisticated artificial retinas.

Other neural-implant research is targeting another frustrating area for medical therapy: paralysis. If distant robotic limbs can be controlled with implantable electrodes, it may also be possible to restore movement to the limbs of patients who have sustained spinal cord injuries.

The problem is on the same order of complexity as the artificial retina, but a number of research groups are tackling it. Dutch neurosurgeon Hans van der Aa has founded an institute called Twin, associated with the University of Twente, to develop such "neuromodulation therapy." The institute, in collaboration with several laboratories in the Netherlands, is developing complex embedded control systems and the related electrode components needed to build effective therapies for paralysis.

Nanotubes integrated with regular array of diamond atoms enable new bio-friendly IC technology

09/12/2005
Argonne National Laboratories has found a way to make diamond a conductor as well as an insulator and semiconductor, opening the door to a new era of all-diamond chips.
...
In general, diamond deposition yields high-performance, long-lasting, radiation-hard dielectric films that can be thin or thick, can be etched alongside silicon components and can be doped either as n- or p-type semiconductors. Diamond's stiffness yields faster resonators, its smoothness yields friction-free microelectromechanical systems and its chemical inertness makes it ideal for bioengineered devices such as human implants.
...
By adjusting the ultrananocrystalline [diamond deposition] process, the lab's researchers have managed to grow nanotubes between the diamond islands, turning what would ordinarily be a dielectric that insulates as well as silicon dioxide into a conductor that conducts as well as aluminum or copper. [The nanotubes are covalently bonded to the diamond at the nanoscale]

More info on diamond as a nanoscale building material:

Water is a hazard for machines in the micron range. In a tiny device, a molecule or two of water can play havoc with the mechanics. Silicon’s chemical bonds attract water. Diamond, on the other hand, is hydrophobic; it gives water the chemical equivalent of the cold shoulder.

Because it is composed solely of carbon, diamond is suitable for biomedical and electronic applications. The body readily will accept a carbon-based MEMS device or nanomachine because carbon is present in every organic molecule. Its composition also makes diamond a good conductor of electricity.

Looking at Sound

2005-11-19T13:10:00.000-08:00

Lately I've been listening a lot to Kate Bush's album Aerial - beautiful, wonderful stuff. The album cover is interesting too - the 'islands' that are reflected in the water are actually the amplitude envelope of a recording of some birds singing.

This idea of 'looking at sound' in different ways has been something I've really enjoyed exploring over the last several years. To help visualize the harmonics in a piece of music, I wrote a program a while back that analyses the frequency content of a sound waveform and creates a spectrogram (spectrum over time) of it, colour coding the intensity levels of each frequency.

I think I've found the bird song shown on the cover - it's 2:25 from the start of the song 'Aerial'. Here's what its spectrogram looks like:

The parallel contour lines that are stacked one on top of each other are the harmonics of the bird song. (A synthesizer's been added to the recording, which has changed the amplitued envelope somewhat and contributed the 'white noise' vertical smears and horizontal tones seen in this spectrogram.)

Here's what a bird singing solo looks like (from the song AerialTal at the 7 second mark):

Once you've learned what to look for, you can look at sound in the frequency domain and sort of recognize individual 'voices' by looking at their harmonic patterns. You can pick out harmonic 'signatures' like this even if there's background noise or other sound sources. It's much tougher to look at a spectrogram and figure out what's going on than it is simply to listen to the sound and figure it out, however. There's must be some pretty awesome signal processing going on in the ear+brain combo...

When I first started writing this, I thought I had a pretty good grasp of how hearing works - you know, vibrations in the air moving the ear drum and getting picked up by little hairs in the inner ear. But this only goes so far... How does the movement of these tiny hairs get turned into something the brain can make sense of? (Especially since there are only around 16,000 of these hair cells in the human cochlea.) This is where it gets totally fascinating. I stumbled across this awesome MIT website that delves into the micromechanics of the inner ear, and has some cool photos and videos of how these tiny hair cells convert sound energy into a form of chemical energy that the brain understands. From the website:
The inner ear performs some very remarkable signal processing. For example, the inner ear can detect motions of the eardrum on the order of a PICOMETER -- i.e., much smaller than the diameter of a hydrogen atom. ... Hair cells are small. But hair cells are themselves complex micromechanical systems whose function relies on an array of even smaller mechanical parts. Displacements of hair bundles generate electrical responses in hair cells via mechanically sensitive ion channels in the cell membrane.

video (165K)
The tip links are tiny filaments only 2nm in diameter. In the video you can see them pulling open little 'trap doors' - opening the 'mechanically sensitive ion channels in the cell membrane' mentioned earlier. (Aside: It's pretty easy to visualize these filaments getting snapped when listening to music at high volume. No more 'turning the volume up to 11' for me...)

These ion channels are basically pores in the cell membrane that allow charged Potassium (K+) ions to move into the cell, which causes the cell to lose polarization. "In order to be able to process sounds at the highest frequency range of human hearing, hair cells must be able to turn current on and off 20,000 times per second. They are capable of even more astonishing speeds in bats and whales, which can distinguish sounds at frequencies as high as 200,000 cycles per second"(ref.)

From The Neurobiology of Harmony by David Benner:
Once frequency and amplitude are converted into action potentials, the biochemical pathway leads sounds from the inner ear along the auditory nerve which is part of cranial nerve VIII through parts of the medulla, pons, midbrain, thalamus, and finally to the auditory cortex of the temporal lobe. The parts of the brain involved in the perception of sound locate its origin and involve the limbic system in the recognition of a given input.

From Music in Your Head by Eckart O. Altenmüller:
After sound is registered in the ear, the auditory nerve transmits the data to the brain stem. There the information passes through at least four switching stations, which filter the signals, recognize patterns and help to calculate the differences in the sound’s duration between the ears to determine the location from which the noise originates. For example, in the first switching area, called the cochlear nucleus, the nerve cells in the ventral, or more forward, section react mainly to individual sounds and generally pass on incoming signals unchanged; the dorsal, or rear, section processes acoustic patterns, such as the beginning and ending points of a stimulus or changes in frequency. After the switching stations, the thalamus—a structure in the brain that is often referred to as the gateway to the cerebral cortex—either directs information on to the cortex or suppresses it. This gating effect enables us to control our attention selectively so that we can, for instance, pick out one particular instrument from among all the sounds being produced by an orchestra. The auditory nerve pathway terminates at the primary auditory cortex, or Heschl’s gyrus, on the top of the temporal lobe. The auditory cortex is split on both sides of the brain. It seems that the way the music is handled in the brain from this point on differs greatly between non-musicians and musicians, and in fact even between individuals. In imaging studies the same music is represented in multiple ways in the brain of a professional musician: as a sound, as movement (for example, on a piano keyboard), as a symbol (notes on a score) and so on. Not so in the brain of an unpracticed listener. Generally, however, rhythm is handled by the left side of the brain and pitch and melody are handled by the right side of the brain.

Harmonics are a set of frequencies that are integer multiples of a common 'fundamental' root frequency. My guess is that, when enough pulses from the frequency detectors for a particular harmonic series fire at around the same time, a 'harmonic detector' neuron is pushed over a trigger threshold. And then, the outputs of these harmonic detector neurons and frequency detector neurons somehow get compared to harmonic profiles stored in memory (e.g. the sound of a voice or of a musical instrument).

By focusing on the harmonic structure that is present in the sound, we are able to focus in on one voice in a crowd, one instrument in a band, isolate signals from noise, spatially locate a sound in a 3D sound field - lots of things our present-day technology has difficulty doing. It provides key information to the brain that allows it to recognize voices, pick out rhymes and rhythms, melodies and harmonies, associate everything with feelings and meaning.

U2's lead singer Bono has noted that "songs are not like movies where you can see them once, twice, three times - they become part of your life. They're more like smells." Music doesn't seem to get registered into memory the same way that visual images do. What you remember is the way the music makes you feel, and the stuff that is repeated several times (chorus, guitar riff, killer bass line). It takes a while to learn the rest, to hang onto it long enough for you to anticipate it fully. Perhaps it's because the brain needs a certain amount of repetition to convert a short term memory into a long term memory (see "Making Memories Stick" by R. Douglas Fields for more info). For whatever reason, music is very much 'in and of the moment'. And it's deeply rooted - it can trigger an emotional and/or physical response, make you want to dance and sing - such a joyous thing. The essence of now, of life.

See also:
Music and the Brain (Scientific American)
Getting a Leg Up on Land - the evolution of four-limbed animals from fish (includes info on how hearing evolved)
Eaton-Peabody Lab (one of the world's largest basic research facilities dedicated to the study of hearing and deafness)
Research into regeneration of damaged inner ear hair cells
Gene therapy stimulates new hair growth in the cochlea

Headspace

2005-11-15T20:07:00.000-08:00

I've recently become quite fascinated with the mechanics of biological systems - how cells work, genetics, the 3D physicality of nanometer sized organic molecules. There are two amazing videos by a company called Hybrid Medical Animation (their demo reel and Stages of Mitosis) that capture the essence of it beautifully.

I've become especially fascinated with neurobiology. A number of years ago I developed a number of adaptive real-time signal processing algorithms for echo cancellation that used a "stochastic iteration" error estimation and adaptive feedback algorithm similar to the learning algorithms used in Neural Networks, and that's when I first started getting interested in how the brain works. Recent advances in brain imaging and neurobiology have really been amazing, and have shown that the brain is much more than the matrix of adaptive electrical elements I used to conceptualize it as - it's a complex organic, evolving, chemical driven 3D environment where dendrites and axons are much more than simple wires, where neurons are not the only cells actively involved in learning, where everything has a role to play. The picture below really helps to drive home how truly organic the brain is:

Neocortex: Output neurons (gold), neocortex neurons (white) (link)

I've been wondering for a while how cells 'know' where they are in the body and the role they need to play and cell structure they need to adopt. Found a good overview (a bit technical, but worth the effort):"Molecular Neurobiology of Development".

It appears that there are gradients of mRNA and proteins that get set up on the ova that identify top/bottom, left/right, front/back:
"The concentration gradient orchestrates a coherent set of cellular behaviors that will eventually result in the proportionate growth of an organ, including the finest details. For example, different scalar concentrations may specify the type of cells and their relative position within the field; the slope of the gradient may be correlated to the degree of growth of the intervening cells, and the direction of the gradient with respect to the compartment may determine polarity."

I guess if you inject stem cells into a damaged heart, the gradients are still there to tell them what kind of cells to become...

Then there are timed genetic programs that control the fate of the cells, including homeobox genes that "encode transcription factors, proteins which turn on other genes. A single homeobox gene can cause a cascade of other genes to be turned on, producing an entire body segment or limb."

And at certain critical points in the development, new markers get established which set up localized chemical gradients to guide the accurate formation of detailed microstructure - e.g. the "match maker" protein SYG-1 acts as a "guidepost" during development, directing two neurons to join.

I can't help but wonder what we will be able to do once we understand how to uniquely determine a cell's "address" by decoding the gradients at it's location and how to alter the genetic blueprint to create novel structures of our own design.

Looking at that image of the neurons in the neocortex, and thinking about dendrites and axons growing along chemical gradients, it strikes me how intrinsically organic we are - axons and dendrites, growing like roots reaching for water, winding through the mind in a mass of complex, interwoven, highly physical fractal connections that define meaning.

Wow.

Brian