How does the synaptic cleft exist?

How does the synaptic cleft exist?

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I'm not asking why the synaptic cleft exists, i.e. what function it holds, rather how.
So I know that the neurotransmitter diffuses across it, it is 20-40 nm wide and contains basal lamina (in NMJs at least), but I cannot find any allusion as to what causes the gap; how the two membranes don't just touch, and how so consistent a distance is created across neurons.
Google has so far failed me on this one, though perhaps I am not searching well enough, any help would be greatly appreciated.

There are membrane proteins that act as structural components of the gap (i.e. the synapses aren't just floating there, they are anchored to each other via membrane proteins).

The most common examples are neurexin (expressed on the pre-synaptic terminal) and neuroligin (expressed on the post-synaptic terminal). Not surprisingly, these proteins are involved in synapse formation in the developping brain, as well as the adult brain (in plastic processes where new synapses are formed). To a first approximation, as synapses are growing, their membrane proteins bind their partners and become anchored. This also leads to intracellular signalling and further maturation of the synapse. That's how synapses know where to attach.

Neuronal Glutamatergic Synaptic Clefts Alkalinize Rather Than Acidify during Neurotransmission

The dogma that the synaptic cleft acidifies during neurotransmission is based on the corelease of neurotransmitters and protons from synaptic vesicles, and is supported by direct data from sensory ribbon-type synapses. However, it is unclear whether acidification occurs at non-ribbon-type synapses. Here we used genetically encoded fluorescent pH indicators to examine cleft pH at conventional neuronal synapses. At the neuromuscular junction of female Drosophila larvae, we observed alkaline spikes of over 1 log unit during fictive locomotion in vivo. Ex vivo, single action potentials evoked alkalinizing pH transients of only ∼0.01 log unit, but these transients summated rapidly during burst firing. A chemical pH indicator targeted to the cleft corroborated these findings. Cleft pH transients were dependent on Ca 2+ movement across the postsynaptic membrane, rather than neurotransmitter release per se, a result consistent with cleft alkalinization being driven by the Ca 2+ /H + antiporting activity of the plasma membrane Ca 2+ -ATPase at the postsynaptic membrane. Targeting the pH indicators to the microenvironment of the presynaptic voltage gated Ca 2+ channels revealed that alkalinization also occurred within the cleft proper at the active zone and not just within extrasynaptic regions. Application of the pH indicators at the mouse calyx of Held, a mammalian central synapse, similarly revealed cleft alkalinization during burst firing in both males and females. These findings, made at two quite different non-ribbon type synapses, suggest that cleft alkalinization during neurotransmission, rather than acidification, is a generalizable phenomenon across conventional neuronal synapses.SIGNIFICANCE STATEMENT Neurotransmission is highly sensitive to the pH of the extracellular milieu. This is readily evident in the neurological symptoms that accompany systemic acid/base imbalances. Imaging data from sensory ribbon-type synapses show that neurotransmission itself can acidify the synaptic cleft, likely due to the corelease of protons and glutamate. It is not clear whether the same phenomenon occurs at conventional neuronal synapses due to the difficulties in collecting such data. If it does occur, it would provide for an additional layer of activity-dependent modulation of neurotransmission. Our findings of alkalinization, rather than acidification, within the cleft of two different neuronal synapses encourages a reassessment of the scope of activity-dependent pH influences on neurotransmission and short-term synaptic plasticity.

Keywords: glutamatergic pH imaging synaptic cleft synaptic plasticity.

Copyright © 2020 the authors.


Trans-cuticular imaging of pHusion-Ex at…

Trans-cuticular imaging of pHusion-Ex at the in vivo NMJ reveals synaptic cleft alkalinization…

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A chemical pH reporter trapped in the cleft at the ex vivo NMJ…

Cleft alkalinization is synchronous with…

Cleft alkalinization is synchronous with Ca 2+ extrusion from adjacent synaptic compartments. A…

Burst-evoked cleft alkalinization is modulated…

Burst-evoked cleft alkalinization is modulated by extracellular pH buffering capacity. A , NMJ…

Activity-dependent pH changes at the…

Activity-dependent pH changes at the mammalian calyx of Held synapse. A , Representation…

Imaging Cac-kisser-pHerry-TM at the ex…

Imaging Cac-kisser-pHerry-TM at the ex vivo NMJ confirms alkalinization within the cleft at…

The bouillabaisse of the synaptic cleft

The synaptic cleft is so small ( under 400 Angstroms — 40 nanoMeters ) that it can’t be seen with the light microscope ( the smallest wavelength of visible light 3,900 Angstroms — 390 nanoMeters). This led to a bruising battle between Cajal and Golgi a just over a century ago over whether the brain was actually made of cells. Even though Golgi’s work led to the delineation of single neurons he thought the brain was a continuous network. They both won the Nobel in 1906.

Semifast forward to the mid 60s when I was in medical school. We finally had the electron microscope, so we could see synapses. They showed up as a small CLEAR spaces (e.g. electrons passed through it easily leaving it white) between neurons. Neurotransmitters were being discovered at the same time and the synapse was to be the analogy to vacuum tubes, which could pass electricity in just one direction (yes, the transistor although invented hadn’t been used to make anything resembling a computer — the Intel 4004 wasn’t until the 70s). Of course now we know that information flows back and forth across the synapse, with endocannabinoids (e. g. natural marihuana) being the major retrograde neurotransmitter.

Since there didn’t seem to be anything in the synaptic cleft, neurotransmitters were thought to freely diffuse across it to being to receptors on the other (postsynaptic) side e.g. a free fly zone.

Fast forward to the present to a marvelous (and grueling to read because of the complexity of the subject not the way it’s written) review of just what is in the synaptic cleft [ Cell vol. 171 pp. 745 – 769 ’17 ] (It is likely behind a paywall). There are over 120 references, and rather than being just a catalogue, the single author Thomas Sudhof extensively discusseswhich experimental work is to be believed (not that Sudhof is saying the work is fraudulent, but that it can’t be used to extrapolate to the living human brain). The review is a staggering piece of work for one individual.

The stuff in the synaptic cleft is so diverse, and so intimately involved with itself and the membranes on either side what what is needed for comprehension is not a chemist but a sociologist. Probably most of the molecules to be discussed are present in such small numbers that the law of mass action doesn’t apply, nor do binding constants which rely on large numbers of ligands and receptors. Not only that, but the binding constants haven’t been been determined for many of the players.

Now for some anatomic detail and numbers. It is remarkably hard to find just how far laterally the synaptic cleft extends. Molecular Biology of the Cell ed. 5 p. 1149 has a fairly typical picture with a size marker and it looks to be about 2 microns (20,000 Angstroms, 2,000 nanoMeters) — that’s 314,159,265 square Angstroms (3.14 square microns). So let’s assume each protein takes up a square 50 Angstroms on a side (2,500 square Angstroms). That’s room for 125,600 proteins on each side assuming extremely dense packing. However the density of acetyl choline receptors at the neuromuscular junction is 8,700/square micron, a packing also thought to be extremely dense which would give only 26,100 such proteins in a similarly distributed CNS synapse. So the numbers are at least in the right ball park (meaning they’re within an order of magnitude e.g. within a power of 10) of being correct.

When you see how many different proteins and different varieties of the same protein reside in the cleft, the numbers for each individual element is likely to be small, meaning that you can’t use statistical mechanics but must use sociology instead.

The review focuses on the neurExins (I capitalize the E to help me remember that they are prEsynaptic). Why? Because they are the best studied of all the players. What a piece of work they are. Humans have 3 genes for them. One of the 3 contains 1,477 amino acids, spread over 1,112,187 basepairs (1.1 megaBases) along with 74 exons. This means that just over 1/10 of a percent of the gene is actually coding for for the amino acids making it up. I think it takes energy for RNA polymerase II to stitch the ribonucleotides into the 1.1 megabase pre-mRNA, but I couldn’t (quickly) find out how much per ribonucleotide. It seems quite wasteful of energy, unless there is some other function to the process which we haven’t figured out yet.

Most of the molecule resides in the synaptic cleft. There are 6 LNS domains with 3 interspersed EGFlike repeats, a cysteine loop domain, a transmembrane region and a cytoplasmic sequence of 55 amino acids. There are 6 sites for alternative splicing, and because there are two promoters for each of the 3 genes, there is a shorter form (beta neurexin) with less extracellular stuff than the long form (alpha-neurexin). When all is said and done there are over 1,000 possible variants of the 3 genes.

Unlike olfactory neurons which only express one or two of the nearly 1,000 olfactory receptors, neurons express mutiple isoforms of each, increasing the complexity.

The LNS regions of the neurexins are like immunoglobulins and fill at 60 x 60 x 60 Angstrom box. Since the synaptic cleft is at most 400 Angstroms long, the alpha -neurexins (if extended) reach all the way across.

Here the neurexins bind to the neuroligins which are always postsynaptic — sorry no mnemonic. They are simpler in structure, but they are the product of 4 genes, and only about 40 isoforms (due to alternative splicing) are possible. Neuroligns 1, 3 and 4 are found at excitatory synapses, neuroligin 2 is found at inhibitory synapses. The intracleft part of the neuroligins resembles an important enzyme (acetylcholinesterase) but which is catalytically inactive. This is where the neurexins.

This is complex enough, but Sudhof notes that the neurexins are hubs interacting with multiple classes of post-synaptic molecules, in addition to the neuroligins — dystroglycan, GABA[A] receptors, calsystenins, latrophilins (of which there are 4). There are at least 50 post-synaptic cell adhesion molecules — “Few are well understood, although many are described.”

The neurexins have 3 major sites where other things bind, and all sites may be occupied at once. Just to give you a taste of he complexity involved (before I go on to larger issues).

The second LNS domain (LNS2)is found only in the alpha-neurexins, and binds to neuroexophilin (of which there are 4) and dystroglycan .

The 6th LNS domain (LNS6) binds to neuroligins, LRRTMs, GABA[A] receptors, cerebellins and latrophilins (of which there are 4)_

The juxtamembrane sequence of the neurexins binds to CA10, CA11 and C1ql.

The cerebellins (of which there are 4) bind to all the neurexins (of a particular splice variety) and interestingly to some postsynaptic glutamic acid receptors. So there is a direct chain across the synapse from neurexin to cerebellin to ion channel (GLuD1, GLuD2).

There is far more to the review. But here is something I didn’t see there. People have talked about proton wires — sites on proteins that allow protons to jump from one site to another, and move much faster than they would if they had to bump into everything in solution. Remember that molecules are moving quite rapidly — water is moving at 590 meters a second at room temperature. Since the synaptic cleft is 40 nanoMeters (40 x 10^-9 meters, it should take only 40 * 10^-9 meters/ 590 meters/second 60 trillionths of a second (60 picoSeconds) to cross, assuming the synapse is a free fly zone — but it isn’t as the review exhaustively shows.

It it possible that the various neurotransmitters at the synapse (glutamic acid, gamma amino butyric acid, etc) bind to the various proteins crossing the cleft to get their target in the postsynaptic membrane (e.g. neurotransmitter wires). I didn’t see any mention of neurotransmitter binding to the various proteins in the review. This may actually be an original idea.

I’d like to put more numbers on many of these things, but they are devilishly hard to find. Both the neuroligins and neurexins are said to have stalks pushing them out from the membrane, but I can’t find how many amino acids they contain. It can’t find how much energy it takes to copy the 1.1 megabase neurexin gene in to mRNA (or even how much energy it takes to add one ribonucleotide to an existing mRNA chain).

Another point– proteins have a finite lifetime. How are they replenished? We know that there is some synaptic protein synthesis — does the cell body send packages of mRNAs to the synapse to be translated there. There are at least 50 different proteins mentioned in the review, and don’t forget the thousands of possible isoforms, each of which requires a separate mRNA.

Old Chinese saying — the mountains are high and the emperor is far away. Protein synthesis at the synaptic cleft is probably local. How what gets made and when is an entirely different problem.

A large part of the review concerns mutations in all these proteins associated with neurologic disease (particularly autism). This whole area has a long and checkered history. A high degree of cynicism is needed before believing that any of these mutations are causative. As a neurologist dealing with epilepsy I saw the whole idea of ion channel mutations causing epilepsy crash and burn — here’s a link —’ve-found-the-mutation-causing-your-disease-not-so-fast-says-this-paper/

Once again, hats off to Dr. Sudhof for what must have been a tremendous amount of work

Synaptic transmission:

The structure of a cholinergic synapse and neuromuscular junction should be known. The acetylcholine receptor in the first image on the left is more better known as nicotinic cholinergic receptor.

In a cholinergic synapse (this is the only synapse you need to know) an action potential increases permeability of the presynaptic membrane by stimulating the Ca2+ ion gated channels to open. This causes an influx of Ca2+ ions into the presynaptic knob down its concentration gradient by facilitated diffusion. The high concentration of Ca2+ ions causes the vesicles of acetylcholine (neurotransmitters) to fuse with the presynaptic membrane. NB: It is best to say acetylcholine than Ach because it gives you more of an understanding and helps with questions if it says ‘acetylcholine’ instead of Ach. If you are going to use Ach it is important that you know what it is. Acetylcholine leaves the presynaptic knob by exocytosis into the synaptic cleft. Acetylcholine diffuses across the synaptic cleft and binds to the cholinergic receptors causing the Na ligand gated channels to open. This causes an influx of Na+ ions into the postsynaptic neurone making the postsynaptic neurone depolarised and if the threshold is met, an action potential is generated. The acetylcholine is removed from the synaptic cleft by the enzyme acetylcholine esterase into products by complementary shapes to prevent a continuous impulse. NB: Acetylcholine esterase can be abbreviated into Ache however it is best also to refer to this enzyme as acetylcholine esterase as it will help you in questions that have this name. The products are actively transported into the presynaptic knob by the use of Pi from ATP into vesicles to make acetylcholine. The Ca2+ ions are actively transported out of the presynaptic knob by the use of Pi from ATP.

Above is an example of excitatory neurotransmitters. This is where the postsynaptic neurone is depolarised leading to an action potential being fired when the threshold is met. Neurotransmitters can also be inhibitory where they hyperpolarise the postsynaptic neurone by opening the K= ion gated channels open.

Neuromuscular junctions work in exactly the same way however:

  • Postsynaptic membrane: The postsynaptic membrane of the muscle is deeply folded to form clefts. This is where acetylcholine esterase is stored. NB: It is important that you say postsynaptic membrane of the muscle and not postsynaptic membrane of a neurone as a postsynaptic neurone is not involved in a neuromuscular junction.
  • Receptors: There are many more receptors on the postsynaptic membrane of the muscle than on the postsynaptic membrane of a neurone.
  • Neurotransmitters: The acetylcholine are excitatory in every neuromuscular junction whereas in the synapse it can be excitatory or inhibitory.

Spatial summation is where many presynaptic neurones connect to one postsynaptic neurone. A small amount of excitatory neurotransmitters can be enough for the threshold to be met in the postsynaptic neurone and causing an action potential to be created. If some neurotransmitters are inhibitory then the overall effect may not be an action potential as it will be difficult to meet the threshold in the postsynaptic neurone. Temporal summation is where there is a quick-fire of two or more action potentials arriving at the same time from one presynaptic neurone. This means more neurotransmitters are released into the cleft making an action potential more likely to occur as the threshold may be met.

Some drugs mimic or inhibit the action of neurotransmitters:

  • If a drug causes an action potential to be triggered, then this is because the drug and the receptor have complementary shapes where it is mimicking the neurotransmitter. These type of drugs are said to be agonists.
  • If a drug does not cause action potential but it is binded to the receptors, then this means that the drug is complementary to the receptor but blocks the receptor so not many receptors are activated. These type of drugs are said to be antagonists.
  • If a drug binds to an acetylcholine esterase, then this means fewer enzyme-substrate complexes will be formed with acetylcholine creating a continuous impulse.
  • If more receptors are stimulated, then this is because the drug releases more neurotransmitters than usual.
  • If less receptors are stimulated, then this is because the drug inhibits the release of neurotransmitters.

NB: Recall of names of drugs and the mechanism of drugs do not need to be recalled in the exam. A piece of information will be given in the exam about a drug and its mechanism and only you have to explain why that has happened which are the bullet points above. These are the only explanations you need to know and are highlighted in green.

Drugs on Synaptic Transmission

Drugs can affect any of the stages in the "life-cycle" of a neurotransmitter.

Drugs that bind with receptors on the post-synaptic (and sometimes pre-synaptic) membrane fall into two groups:

Agonists: Bind to receptors and simulate or enhance a neurotransmitter's actions (i.e., opening ion channels and causing EPSPs or IPSPs).
Antagonists: Have the opposite effect of agonists by blocking the receptors and inactivating it (usually by taking up the space but without specifically causing the opening of the channel or the operation of the secondary messenger). The neurotransmitter's effect is nullified or diminished.
The table below lists some common drugs, they action in the brain and their observable behavior:

Acetylcholine receptor agonist

Smokers: relaxation, alertness, reduced desire for food.
Non-smokers: Nausea, vomiting, cramps, and diarrhea.

1. Reduces flow of Ca2+ into cells
2. GABA agonist
3. Increases number of binding sites for glutamate
4. Interferes with some secondary messenger systems

Low doses effect is excitatory.
Moderate to high doses effect is inhibitory.

Blocks reuptake of dopamine and norepinepherine

Feelings of well-being and confidence.
Reduced desire for sleep and food.

Opiates (heroin, morphine, codeine)

Pain suppression and euphoria.
Suppresses cough and diarrhea

Serotonin receptor agonist

Alcohol inhibits neurotransmission in two ways. First, it inhibits the excitatory channels on the postsynaptic neuron. Next, it lowers the rate of action potentials from the presynaptic neuron.

At synapses where adenosine is the primary neurotransmitter, a high postsynaptic firing rate leads to sleepiness. Caffeine inhibits sleepiness by inhibiting adenosine neurotransmission.

Nicotine affects neurotransmission by causing more action potentials in the presynaptic neuron and by causing more dopamine to be released per vesicle.

Cocaine provides a sense of euphoria by blocking the reuptake of dopamine by the presynaptic neuron. This leads to a higher dopamine concentration in the synapse and more postsynaptic firing.

The mechanism by which heroin affects neurotransmission is unclear, but it is thought to increase the rate of vesicle fusion in the presynaptic neurons that use dopamine as a neurotransmitter.


In the first part of the guided inquiry activity, the students will estimate the width of the synaptic cleft of the synapses shown in Figures 1A and 2. In the following, I refer to the two models shown in these figures as “Morphometric Synapse Model” and “Schematic Synapse Model,” respectively.

By the time the students start Part 1, they should be familiar with the relevant metric prefixes and the corresponding values shown in Table 1. The students should also be able to relate the results obtained through the inquiry activity to some fundamental dimensions of nerve cells in the central nervous system, such as the range of soma sizes (granule cells in the cerebellum:

4 μm Betz cells of the motor cortex: 100 μm) and the range of diameters of axons (0.1–10 μm) among cells.

Prefix . Symbol . Multiplication Factor . Power .
(no prefix) 1 10 0
centi c 0.01 10 −2
milli m 0.001 10 −3
micro μ 0.000001 10 −6
nano n 0.000000001 10 −9
Prefix . Symbol . Multiplication Factor . Power .
(no prefix) 1 10 0
centi c 0.01 10 −2
milli m 0.001 10 −3
micro μ 0.000001 10 −6
nano n 0.000000001 10 −9

The metric prefix is a modification of the basic unit of measure to indicate the value of the unit. Examples: 1 μm (micrometer) = 1·10 −6 m 5 ms (millisecond) = 5·10 −3 s.

For the estimation of the synaptic dimensions, the students are provided with printouts of the model synapses shown in Figures 1A and 2, including a description of the labeled components. The only other information they receive is that the diameter of the presynaptic axon is 0.5 μm. Based on this information, the students are asked to estimate the dimensions of the following two components of the two model synapses: (1) length of the presynaptic terminal (defined as the dimension perpendicular to the axon shaft) and (2) width of the synaptic cleft. To estimate these dimensions, they should follow these steps:

Measure (in millimeters) the diameter of the axonal shaft on each of the two printouts.

Assuming that the diameter of the axonal shaft is 0.5 μm, use the results obtained in step 1 to calculate the magnification factor of the drawings shown in each of the two figures. This is done by dividing the diameter measured on the drawing by 0.5 μm. Remember to use identical units of measure for your calculations.

Measure (in millimeters) the length of the presynaptic terminal (defined as the dimension perpendicular to the axon shaft) on each of the two printouts.

Use the magnification factors calculated in step 2 and the corresponding results obtained in step 3 to estimate the actual lengths of the presynaptic terminals shown in the two drawings.

Measure (in millimeters) the width of the synaptic cleft on each of the two printouts.

Use the magnification factors calculated in step 2 and the corresponding results obtained in step 5 to estimate the actual width of the synaptic clefts shown in the two drawings.


Let us assume that, on the printout of the Schematic Synapse Model, the diameter of the axonal shaft is 40 mm (please note that this value may vary among different printouts) – that is, this structure is 80,000 times enlarged, compared to the actual dimensions of a typical axon, here assumed to be 0.5 μm. The length of the presynaptic terminal (determined on the same printout to be 85 mm or 0.085 m) is, therefore, 8.5·10 −2 m ÷ 80,000 = 1.06·10 −6 m or 1.06 μm or ≈1 μm. Applying the same procedure, the width of the synaptic cleft is estimated to be 475 nm (≈0.5 μm).

Similarly, application of the above procedure to the Morphometric Synapse Model yields ≈1 μm for the length of the presynaptic terminal and ≈20 nm for the width of the synaptic cleft.

Evaluation of the Results

Educational models of chemical synapses, like the one shown in Figure 2, generally provide a good indication of the relative proportions of the presynaptic terminal and the axon from which this terminal emerges. For example, in the adult visual cortex, terminal lengths between 0.5 μm and 2.2 μm, with a mean of 1.2 μm, have been measured (Stettler et al., 2006). Axon diameters in the central nervous system typically range between 0.1 μm and 10 μm, but thinner axons are the most abundant (Perge et al., 2012). Thus, a ratio of roughly 2:1 of the length of the presynaptic terminal to the diameter of the axon shaft, as depicted in Figure 2, is well within the range of the proportions of axons and terminals found in the central nervous system.

On the other hand, a width of 0.5 μm of the synaptic cleft, as indicated by the Schematic Synapse Model, is far off – roughly by a factor of 25. Electron microscopy studies have shown that the distance between the apposed synaptic membranes typically ranges between 15 nm and 25 nm (Peters et al., 1991 Zuber et al., 2005). As will be demonstrated in Part 2, this severe distortion of the actual dimension of the synaptic cleft in many educational models of chemical synapses, without mentioning that the dimensions of the synaptic components are not drawn to scale, has serious consequences for the predicted impact on neurotransmitter diffusion time and concentration of transmitter molecules in the synaptic cleft, and thus for the functioning of the synapse.

By contrast, the Morphometric Synapse Model presented in Figure 1A depicts realistically the relative dimensions of axon diameter versus presynaptic terminal length and synaptic cleft width. If the diameter of the axon is 0.5 μm, then the presynaptic terminal will be

1 μm long and the synaptic cleft will be

20 nm wide. Furthermore, the synaptic vesicle shown in Figure 1B will then have a diameter of

40 nm, a value that falls well within the size range of synaptic vesicles containing classical transmitters such as glutamate (Zhang et al., 1998).

Enzymatic Degradation

The activity of some neurotransmitters is terminated by degradation by an enzyme that is in the synaptic cleft. These neurotransmitters include acetylcholine and ones that are neuropeptides, meaning they are chain of amino acids. A enzyme binds to the neurotransmitter and breaks it apart so that the neurotransmitter can no longer fit into a receptor on the receiving cell. Some nerve toxins used as chemical warfare or pesticides block the activity of these enzymes. The nerve gas Sarin works by blocking the activity of acetylcholinesterase, the enzyme the degrades acetylcholine.

Cryo-electron tomography and synaptic transmission in the brain

The brain is by far the most complex and one of the most efficient biological structures known to man. A human brain consists of approximately 86 billion highly interconnected nerve cells, or neurons. The ability of higher organisms to respond quickly to external stimuli, to create tools and organised behaviour for survival, as well as, in humans, to support abstract thought and consciousness is crucially linked to the capacity of neurons to exchange information and create short or long-term paths for its transfer among different areas of the brain. Unlike artificial devices, like computers, in which information is created and manipulated in the form of electric currents flowing within tightly connected electronic circuits, the neurons in the brain maintain their individuality as cells, and mostly communicate with each other by exchanging chemical species, known as neurotransmitters. Over hundreds of millions of years of evolution, the process through which neurotransmitters are exchanged between neurons has been optimised to an incredible level of efficiency and reliability. Only recently, however, have we been able to gain some insight into the complex biochemical mechanisms that regulate this process.

Neurons communicate with each other by imparting neurotransmitters via contact points, the so-called neuronal synapses. Designua/

How neurons exchange information
Neurons have a very characteristic morphology compared to other cells, and they are characterised by a long and thin structure, called axon, protruding from the cell body and terminating in the form of a ramified group of branches containing presynaptic terminals. Neuronal synapses are contact points between neurons, where information is transferred from a presynaptic to a postsynaptic cell. In an excited neuron, the arrival of an electric signal from the cell body to the synapses can cause the fusion of small vesicles filled with neurotransmitter molecules with the synaptic membrane and release its content to the extracellular space between the two neurons, known as synaptic cleft. The binding of the neurotransmitter to the postsynaptic receptor triggers chemical processes that result in the creation of electrical signals in the postsynaptic neurons, thus completing the information transfer.

The transfer of information between individual neurons in the brain occurs via a carefully regulated release of chemical

The neurotransmitter release is a very fast and complex process, which requires a precise spatio-temporal coordination of biochemical processes involving presynaptic proteins. Not every synaptic vesicle can be released: other biochemical processes are involved in priming some of the vesicles for release, to form the so-called readily releasable pool. These processes are mostly carried out by macromolecular protein complexes, which, in many cases, exist in transient form and survive only for the time required for them to exert their function.

In cryo-EM, samples are cooled so fast that water molecules don’t have time to transform into a crystalline state. PolakPhoto/

Imaging neurotransmitter release
Electron microscopy (EM) can be used to image biological samples, similar to conventional optical microscopy. In EM, the use of a beam of electrons, rather than visible light, makes it possible to reach a much higher level of resolution than standard microscopy. During EM observation, however, samples have to be kept in a vacuum. This is major problem in the case of biological systems, because water, which constitutes a large component of the sample, evaporates in the vacuum, leading to irreparable sample damage. Chemical fixation followed by controlled dehydration can be used to partially solve this problem, which makes EM suitable in the study of the structure and function of cellular organelles. Nonetheless, this technique still causes sample alterations that preclude the study of cellular processes at a molecular level.

Cryo-electron tomography
In cryo-EM, samples are cooled so fast that water molecules do not have enough time to reorient and form ice crystals, which brings them to a glass-like solid form, called a vitreous state. Dr Vladan Lučić at Max Planck Institute of Biochemistry is an expert in the use of cryo-EM in combination with tomography, a method in which multiple images of a sample with different orientations are combined to form a three-dimensional image (tomogram). This approach yields high resolution, three-dimensional images of fully hydrated, vitrified cellular samples, preserved in their native environment and state. Using this method, Dr Lučić and his collaborators have for the first time been able to image protein complexes and vesicles, both at synaptic ends, ready to release neurotransmitters, and in the process of being transported along an axon. This is an important result, as it confirms that the vesicles and the protein complexes involved in the releases of the neurotransmitters are likely to be synthesised in the cell body and then transported through the axon to the synapses, and provides a simultaneous view of both the protein cargo and the lipid membranes involved in the transport.

Synaptic vesicles and neural activity
Cryo-electron tomography experiments carried out on biochemically isolated synapses from rodent brains show that, at the active zone, which is a synaptic area where neurotransmitters are ready to be released, the synaptic vesicles are kept tethered to the synaptic membrane by different types of filaments, which, together with filaments that interlink vesicles, act as the main structural elements organising the vesicles. To understand the function and role of these filaments in the neurotransmitter release process, Dr Lučić and his collaborators have developed automated software procedures that make it possible to analyse the morphology, precise location and interrelation of these complexes at synapses imaged under different release-relevant states. They found that these filaments are dynamic structures that respond to synaptic stimulation and regulate the clustering of the synaptic vesicles by limiting vesicle dispersion at rest and allowing the vesicles to mobilise for release during synaptic activity.

Cryo-electron tomography has the potential to provide a detailed molecular picture of the mechanism of neurotransmitter release at
synaptic membranes.

Based on these findings, Dr Lučić has proposed a structural model of neurotransmitter release, in which synaptic vesicles are initially linked to the synaptic membrane via long tethers, and may acquire multiple, shorter tethers in subsequent steps. This change in their structural organisation makes the vesicles primed for the release of neurotransmitters in the synaptic cleft.

Three-dimensional view of a synapse: A indicates the analysed area. B shows 3D segmentation of synaptic vesicles (yellow), synaptic vesicle connectors (red), and synaptic vesicle tethers (blue). C and D show a synaptic vesicle connector (C) and a tether (D). Copright © 2010 Fernández-Busnadiego et al.

Towards a molecular model of neurotransmitter release
Despite the unprecedented level of insight into the mechanism of synaptic activity made possible by cryo-electron tomography, a number of technical issues hamper the application of this method to fully unravel the complexity of vesicle priming and neurotransmitter release at synaptic membranes. One of the intrinsic advantages of cryo-electron tomography is that all components of a given sample are imaged at the same time. By contrast, optical microscopy can be used to image only those molecular species that are artificially labelled and made fluorescent. This fact complicates enormously the identification of molecules and their complexes in cryo-electron tomography, except in the case of very large complexes of distinct shape.

To address this limitation of cryo-electron tomography, Dr Lučić and his collaborators are currently pursuing two approaches. One of them consists in analysing synapses where a protein is genetically removed. This provides hints on the molecular identity of the structures that are missing compared to the unmodified synapses. The second approach relies on the development of template-free software for the detection and classification of membrane-bound complexes in cellular cryo-electron tomography that contain large number of different proteins. Some of the protein classes obtained with this method are sufficiently homogeneous to allow averaging using available procedures.

This work has already led to a tentative identification of some protein complexes, based on their average structures and cellular location, and it is the first step toward the application of cryo-electron tomography to the direct detection, localisation and identification of protein complexes involved in synaptic transmission within their native cellular environment.


Personal Response

In which fields, in addition to our fundamental understanding of brain function, will your work have the largest impact?

While this work is guided by our interest in synaptic transmission, the method we developed is more general. It can be applied to other cellular targets where vesicles play a prominent role, such as the vesicular transport and the secretory system. Furthermore, we already extended our procedure to analyse molecular complexes that bridge the synaptic cleft, thus expanding the applicability to other types of cellular junctions, such as those prominent in the immune response and the development.

4. Plastic Interactions within the Synaptic Cleft

SAMs are strategically positioned to contribute to synaptic plasticity, given that they can alter synapse structure and function through their ability to sculpt and regulate synaptic protein interaction networks. Below we highlight several important mechanisms that have come to light that regulate SAMs, their diversity, and their functions in a synaptic activity-dependent way. We further present supporting examples to illustrate the general themes ( Figure 3 ).

SAMs can contribute to synaptic plasticity. SAM function can be regulated by synaptic activity through different processes. Protein levels can change (1) as a result of altered localization targeting a protein to or away from the synaptic membrane surface (1a), protein synthesis (1b), protein degradation (1c), and ectodomain shedding (1d). The availability of members within a broad portfolio of potential partners can be altered (2). SAMs can be diversified through alternative splicing (3). SAMs can be repositioned in the synaptic cleft (4). Protein interactions supported by SAMs can be modulated by astrocytic factors (5). Details are as discussed in the text.

4.1. Alteration of SAM Protein Levels in the Synaptic Cleft

It has long been held that synaptic protein abundance is implicated in synaptic plasticity. In particular, altering the abundance of a specific SAM at a synapse could fundamentally impact the development, maintenance, and ultimate elimination of that synapse. A number of studies have used quantitative proteomics of synaptosomal fractions to correlate synaptic protein abundance (including those of SAMs) to events implicated in synaptic plasticity, for example, the long term synaptic adaptions that accompany the administration of drugs of abuse. Repeated morphine administration robustly downregulated CNTN1, L1CAM, neurocan, and OPCML in striatal presynaptic fractions [27], while in a second study neurexin, NCAM, and NTM protein levels decreased more than 40% in rat forebrain synaptosomal fractions, though in this case OPCML protein levels were unaltered [28]. Importantly, these studies showed that the abundance of synaptic proteins was altered in a highly selectively way. Of 175 proteins that could be identified proteomically, only 30 were robustly and consistently altered by morphine treatment (i.e., 17%), indicating that the SAMs that were altered represented highly significant changes [27]. In other studies, experience dependent plasticity induced in animals by trimming their whiskers to cause sensory deprivation resulted in

30% lower levels for the SAMs Pcdh1, ICAM5, Plexin-A1, and Lphn 3 in juvenile mice (a period where synaptogenesis peaks) [29]. Also in this latter study, the protein abundance was only very selectively altered only a small number of proteins were affected which included specific SAMs, while 95% of the 7000 tentative synaptic proteins examined showed no significant changes [29]. The above proteomic studies signify that the protein abundance of SAMs can change in response to events triggering synaptic plasticity. However, several caveats exist. These proteomic approaches offer only a global view of protein abundance, profiling changes in protein levels averaged over a large, heterogeneous population of synapses pooled together from many different kinds of neurons and supporting glial cells. In addition, only those proteins that are technically accessible were monitored, that is, only those proteins which were extracted in sufficiently abundant quantities to enable their detection and analysis by mass spectrometric methods [30].

How do protein levels for a specific SAM change in response to synaptic activity at a specific, single synapse or just a small subset of select synapses? Several processes have been identified that modulate SAM protein levels at the level of a single synapse, altering synapse morphology and stabilizing (or destabilizing) synaptic strength on a very local scale in response to synaptic activity (see (1a)–(1d) in Figure 3 ).

SAMs can accumulate or be depleted from membrane surfaces in the synaptic cleft as a result of altered stability, for example, due to loss of stabilizing partners, recruitment, trafficking, internalization, and/or phosphorylation of cytoplasmic tails. For instance, levels of neurexin 1β at the synaptic membrane rise in response to neural activity, apparently due to an increase in stability (or suppressed dynamics) at the synaptic terminal [31]. NLGN1 and NLGN3 have increased surface membrane levels upon chemically induced LTP and decreased levels after LTD as a result of being dynamically exchanged at the postsynaptic membrane through active cytoskeleton transport [32]. In addition, surface expression of NLGN1 is also increased through CAMKII phosphorylation of its cytoplasmic tail in response to synaptic activity [33]. Other SAMs such as OPCML, CNTN1, and cadherins also display decreasing or increasing protein levels in the synaptic cleft in response to synaptic activity as a result of internalization into the cell or mobilization to the synaptic membrane surface [34�].

Protein levels can rise in the synaptic cleft as a result of activity-induced expression via local protein synthesis at the synapse (recently reviewed in [38]). For example, expression of LRRTM1 and LRRTM2 (synaptic organizers that induce presynaptic differentiation) increases as a function of synaptic activity because influx of Ca2+ into the postsynaptic neuron following NMDA-receptor activation induces nuclear Ca2+-dependent transcription [39]. α-Dystroglycan expression is also upregulated by prolonged increased neuronal activity at inhibitory synapses in the CNS elevating its protein levels [40]. In addition, local translation of DSCAM in dendrites has been shown to be rapidly induced by synaptic activity [41].

SAM levels can also decrease at synapses as a result of degradation, thereby regulating synapse development and survival. Evidence is building that highly targeted protein degradation takes place at synapses locally and that it can be regulated by synaptic activity (for recent review see [38]). Intriguingly, elegant studies have revealed that the C. elegans SAM, SYG-1, can locally inhibit an E3 ubiquitin ligase complex that tags proteins for degradation, protecting adjacent synapses from elimination [42].

One particular form of proteolysis, ectodomain shedding, is now widely documented to regulate SAM protein levels in the synaptic cleft. During shedding, the extracellular domain of a SAM is proteolytically released from its transmembrane segment or its GPI anchor that tethers it to the synaptic membrane. Liberating the SAM ectodomain permits the protein interactions and extracellular matrix to be remodeled within the synaptic cleft. Ectodomain shedding is involved in structural as well as functional synaptic plasticity and impacts key processes like LTP and LTD (for recent reviews see [43, 44]). Exactly where the released ectodomains end up is unclear. Do they remain in the synaptic cleft, binding and blocking their normal protein partners from forming trans-synaptic interactions? Or are the shed ectodomains lost from the synaptic cleft, diffusing outwards to affect other neighboring synapses? Alternatively, are they perhaps simply degraded locally?

Both presynaptic as well as postsynaptic SAMs have been demonstrated to undergo ectodomain shedding in vitro and in vivo. Activity-dependent proteolytic release has been shown for many well-known SAMs, including neuroligins, neurexins, calsyntenins, SIPRα, ICAMs, LARs, Slitrks, and nectins, and their release is executed by various proteases including matrix metalloproteases, ADAM proteases, and alpha/gamma-secretases [14, 43, 45�]. The downstream consequence of ectodomain shedding varies. In the case of the postsynaptic adhesion molecule NLGN1, shedding destabilizes the presynaptic partner neurexin 1β at synapses and decreases the presynaptic release probability of synaptic vesicles, thereby depressing synaptic transmission [48, 50]. Ectodomain release of NLGN1 has relevance for disease, because it is promoted by epileptic seizures [50]. Release of the Sirp α ectodomain has a completely different consequence, because it promotes synapse maturation [51]. Likewise, ectodomain release of CLSTN1, which is found on the postsynaptic membrane of inhibitory and excitatory synapses, permits the transmembrane stub and Ca2+-binding cytoplasmic domain to be internalized and accumulate in the spine apparatus where it is thought to carry out a role in postsynaptic Ca2+- signaling [54].

Taken together, multiple processes exist that regulate protein levels of specific SAMs in the synaptic cleft of single synapses in response to synaptic activity.

4.2. Availability of a Broad Portfolio of Different SAMs Containing Variable, Synergistic, and Competing Partners

It is estimated that there are more than 470 putative cell adhesion molecules in humans [55], although how many of these are expressed in the brain and are synaptic is not known. Nevertheless, a broad portfolio of SAMs has been validated to date and it provides a powerful mechanism to generate a myriad of different possible interactions, some of which can be affected by synaptic activity, thereby contributing to mechanisms of synaptic plasticity (see (2) in Figure 3 ). Diversity is achieved in several ways. Most SAMs are modular in nature and use a combinatorial approach to build up their extracellular region by alternating different structural modules, for example, Ig domains, FN3 domains, and cadherin EC domains ( Figure 1 ). In addition, most SAM families contain several members that, while sharing a conserved domain structure, vary in amino acid sequence. In some families, individual members are diversified even further through alternative splicing of their mRNA, inserting, deleting, or exchanging anywhere from one to more than a hundred amino acids in the encoded protein. For instance, more than a thousand splice variants have been demonstrated for neurexins (discussed below).

The portfolio of SAMs can be expanded even further on a functional level in two key ways. First, SAMs can assume evolving functions over time, carrying out one function during the early stages of brain development, while connectivities are being formed, and then switching to another function in the mature adult brain. For example, early during synapse development, neuroligins and LRRTMs appear to compensate for one another however once synapses have formed, neuroligins and LRRTMs affect excitatory synaptic transmission differently [56]. Likewise, during early development cadherins are important for synapse adhesion, stabilization, and synaptogenesis in young neurons however once mature synapses have formed, they no longer are needed to keep neuronal and synaptic structures in place but appear to play a role in signaling, structural plasticity, and cognitive function [34]. Second, certain SAMs appear to work together synergistically, generating new functions that do not extend to the individual members alone. Case in point, different combinations of protocadherin family members form dimeric cis-complexes that oligomerize into larger tetrameric trans-complexes the functional roles of these different species are still being worked out [57, 58]. Members of different families can also interact with each other in a mix-and-match approach. For example, cadherins bind each other to form trans-complexes spanning the synaptic cleft, but they also can bind protocadherins side-by-side forming cis-complexes [34].

Given such a broad portfolio of SAMs, how different are the proteins functionally or are many of them redundant? The extent to which different SAMs carry out substantially different functions or are redundant is controversial. Some SAMs clearly have discrete and different biological functions. For example, NLGN1 can induce synapse formation in young primary hippocampal cultures, but SynCAM1 cannot [59]. Members of the same SAM family can also have dramatically different roles NLGN2 is found exclusively at inhibitory synapses, while NLGN1 is found predominantly at excitatory synapses [23]. Likewise, Slitrk1 and Slitrk3 promote excitatory versus inhibitory synapse formation, respectively [60, 61] However, equally so, SAMs can also demonstrate functionally redundant actions. For instance, LRRTM1, LRRTM2, NLGN1, and NLGN3, proteins that increase synapse numbers in vitro, appear functionally redundant because only knockdown of all four proteins together decreases the number of formed synapses significantly [62]. Thus, though many SAMs exist, their exact functional roles and the extent to which these are unique or overlap needs to be further investigated, both alone and in the broader context of the synaptic cleft.

The power of a broad portfolio of SAMs binding each other and sculpting interactomes within the synaptic cleft is beautifully illustrated by the complex interaction network that has been revealed centered on neurexins. Presynaptically tethered neurexins reach across the synaptic cleft to bind postsynaptic ligands such as the neuroligins, LRRTMs, and α-dystroglycan, forming trans-synaptic bridges ( Figure 4(a) ). Neurexins also recruit calsyntenins, though whether this interaction is direct or indirect is debated [14, 63, 64]. At excitatory synapses, neurexins extend across the synaptic cleft to bind LRRTMs or NLGN1 promoting excitatory synapse development [23, 65�] ( Figure 4(b) ). Because these postsynaptic partners utilize the same or an overlapping binding surface on neurexin, LRRTM2 and NLGN1, for example, compete with each other for neurexin binding, though the functional consequences are not clear [56, 65, 66]. In contrast, at inhibitory synapses, neurexins form a trans-synaptic interaction with NLGN2 promoting inhibitory synapse development [23]. However, competing with this interaction, the postsynaptic adhesion molecule MDGA1 binds NLGN2 tightly side-by-side forming a cis-complex on the dendritic surface that prevents the neurexin:NLGN2 trans-synaptic bridge, thereby decreasing inhibitory synapse development [16, 17] ( Figure 4(c) ). Also at inhibitory synapses, neurexin 1α binds to α-dystroglycan or neurexophilin 1 (NXPH1) in a mutually exclusive manner. One consequence of α-dystroglycan engaging the neurexin 1α L2 domain is that it prevents binding of neuroligins to the distant neurexin 1α L6 domain suggesting that an (allo)steric mechanism regulates these protein partner interactions [68], (refer back to Figure 1 ). Therefore, the neurexin-centered interactome provides examples of how SAMs can compete with each other for binding partners in cis or in trans and also be subject to (allo)steric mechanisms that regulate protein partner interactions.

Synaptic protein interaction network coordinated by neurexins. (a) Neurexins (blue ovals) bind many protein partners tethered to the postsynaptic membrane including neuroligins, LRRTMs, α-dystroglycan, calsyntenins (CLSTN), and the GABAA-receptor, as well as partners that are secreted such as neurexophilins. (b) NLGN1 and LRRTM2 can both bind neurexins at an overlapping binding site generating two competing trans-interactions. (c) Neurexins and MDGA1 can both bind NLGN2 at an overlapping binding site generating competing cis- and trans-interactions.

It is possible that different SAMs interact with each other in a series of sequential and concerted steps to develop and regulate synapses see also recent review by [69]. Revealing such a playbook of interactions will be no easy task because it is complex to accurately assess SAM function. Protein interactions that occur in vitro in a controlled experimental setting may not occur in vivo in the synaptic cleft or only under select circumstances. Likewise, SAM functions may exist in vivo that are not easily measurable in vitro. By way of illustration, neurexins are synaptogenic in vitro in coculture assays suggesting they are essential to form synapses, yet, in vivo, triple knockout of all three alpha- or beta-neurexins does not prevent synapse formation [70, 71]. Likewise, CNTNAP2, considered a bona fide SAM, does not appear important for synapse formation in and of itself, rather it prevents the elimination of new synapses in some way based on live imaging studies through cranial windows in mice [72]. Taken together, the broad portfolio of SAMs present in mammalian brain appears critical to generate diverse, adaptable protein interaction networks that mediate the different stages of a synapse, starting from its initial formation to its ultimate elimination, and to permit activity-dependent regulation once it has formed.

4.3. Diversification of SAMs through Alternative Splicing

One important mechanism to generate diversity of SAMs in the nervous system that deserves special attention is the process of alternative splicing, which has been shown to be regulated by synaptic activity in some cases (see (3) in Figure 3 ). Alternative splicing provides a very efficient and genetically 𠇌ost-effective” mechanism to generate a large panel of proteins that share a common scaffold but each differ from one another to some extent. Alternative splicing of mRNA transcripts result in insertions, deletions, and substitutions of amino acids in the encoded protein and can involve single residues, small inserts, or even complete domains. Several well-known SAM families undergo alternative splicing of their mRNAs generating a portfolio of protein molecules with altered properties and function.

Neurexins form one of the best studied families of SAMs diversified through alternative splicing. Neurexins are encoded by three genes (1, 2, and 3) that each produce a short beta form and a long alpha form, by virtue of two different promoters [23] see also Figure 1 . Single molecule mRNA sequencing of tens of thousands of neurexin mRNAs has demonstrated that there are at least

1,400 variants by one report and more than 2,000 variants by another in the adult mouse brain [73, 74], though the transcripts are not all equally abundant [74]. Alternative splice inserts can be incorporated at six places in the extracellular region of neurexin 1α (SS#1 through SS#6), adding polypeptide inserts of up to 30 amino acids at five of these insertion sites see Figure 1 and [23, 74]. Incorporation of splice inserts has functional consequences because several inserts have been shown to regulate the interaction of neurexins with different postsynaptic partners. For example, incorporation of SS#2 in the L2 domain of neurexin 1α decreases its binding to α-dystroglycan, while SS#4 regulates the affinity of neurexins to postsynaptic partners such as neuroligins, LRRTMs, α-dystroglycan, cerebellin precursor protein, and latrophilin/ADGRL (recently reviewed by [23, 68, 75]). Proteomic quantitation has confirmed that distinct neurexin splice variants bind different amounts of protein partners, corroborating a mechanism whereby alternative splicing regulates the binding affinity of neurexins for different ligands in vivo [76]. From a biochemical and protein structural perspective, SS#2 and SS#4 change the affinity of Ca 2+ -binding sites central to protein interaction sites on the L2 and L6 domains, while SS#4 also induces structural plasticity because it can adopt multiple conformations [77�]. From a functional perspective, mice engineered to constitutively include SS#4 in neurexin 3α show a decrease in synaptic strength and impaired LTP in vivo because postsynaptic AMPA-receptor levels are decreased at the synapse (as a result of increased AMPA-receptor endocytosis), although the underlying mechanism is not clear [80]. For most neurexin splice inserts, however, their effects on protein structure and function are not well delineated. Likewise, the function of rare neurexin splice variants, in which multiple domains are deleted, is also not known, nor if these yield functional proteins in the first place [74].

The very large portfolio of neurexin alternative splice forms is strategically positioned to play an important role in synaptic plasticity. In the mammalian brain, specific neurexin splice forms demonstrate cell type specific distributions and brain region specific expression both at the mRNA as well as the protein levels [73, 76, 81]. Importantly, incorporation of certain splice inserts is neuronal activity dependent, and an altered splicing profile can be reversed [82�]. For example, analysis of mRNAs in single medium spiny neuron cells (MSNs) demonstrated that neurexin 1α and neurexin 1β are prevalent in D1R-MSNs, but much less so in D2R-MSNs, and mostly contain the SS#4 insert [81]. However, exposure to repeated cocaine administration, a circumstance triggering synaptic plasticity, reduces neurexin 1 mRNA levels in D2R-MSNs even further and alters the profile of splice forms [81]. Therefore, alternative splicing of neurexins generates diversity of protein structure and function, and it can be regulated by events linked to synaptic plasticity.

Other SAM families are regulated by alternative splicing in their extracellular domain as well, altering the affinity with which they bind protein partners in the synaptic cleft. These include the neuroligins where splice inserts regulate interactions with neurexins (refer back to Figure 1 , [85�]) PTPδ and PTPσ where splicing regulates binding to Slitrks, interleukin-1 receptor accessory protein (IL1RAP), and SALM3 [89�] and the family of adhesion GPCRs where alternative splicing alters the domain composition of the extracellular region and consequently the profile of interacting protein partners [95].

4.4. Altered Location of SAMs within the Synaptic Cleft

The advent of powerful high resolution microscopy techniques has revealed that SAMs can be redistributed within the synaptic cleft in response to synaptic activity (see (4) in Figure 3 ). Recent studies show that the synaptic cleft is made up of structurally distinct subcompartments and SAMs can segregate to different regions of the cleft. Upon synaptic activity, however, certain molecules can move within or to the periphery of the synaptic cleft. The impact of these redistributions on synaptic function, however, is not clear. For instance, SynCAM1 and EphB2 receptor tyrosine kinase (EphB2) are two postsynaptic SAMs with different roles. SynCAM1 induces synapse formation and subsequently also maintains excitatory synapses, while EphB2 promotes excitatory synaptogenesis in the rapid early phase of synaptogenesis before neurons mature. By tracking SynCAM1 and EphB2 in the synaptic cleft at excitatory synapses, Perez de Arce and coworkers demonstrated that SynCAM1 is located around the cleft's edge while EphB2 is embedded deeper within the central PSD region [96]. Strikingly, upon application of an LTD paradigm, SynCAM1 underwent redistribution on the surface of the synaptic membrane forming puncta of increasing size, an intriguing finding given that SynCAM1 regulates LTD in vivo and suggesting this redistribution has functional significance [96]. Another SAM, N-cadherin, forms trans-synaptic bridges with N-cadherin molecules tethered to the opposing synaptic membrane. N-cadherin plays an important role presynaptically by regulating synaptic vesicle recruitment and recycling, and postsynaptically in spine remodeling and trafficking of AMPA-Rs, which is important for hippocampal LTP [97]. Superresolution microscopy has shown that N-cadherin localizes predominantly as puncta at the periphery of synapses and to a much lesser extent along the synaptic cleft in unstimulated cultured hippocampal neurons [97]. However, upon synaptic stimulation followed by a rest period, N-cadherin distributes broadly throughout the synaptic cleft [97]. Thus an increasing body of work shows that SAMs can be redistributed as a result of synaptic activity, likely altering protein interactomes in the synaptic cleft. How different SAMs are redistributed and the impact of such redistribution on synaptic function remain to be further elucidated.

4.5. Astrocytic Control of SAMs

A fascinating development has been the demonstration that astrocytes (a type of glial cell found interspersed between neurons which can ensheath synapses) secrete factors that modulate the action of SAMs (see (5) in Figure 3 ). During the development of the nervous system, astrocytes regulate synapse formation and remodeling, impacting synapse number through their ability to promote the formation and elimination of synapses [98]. A single mouse astrocyte can ensheath more than 100,000 synapses [99]. In the mature brain, astrocytes also can modulate synaptic plasticity [98]. Immature astrocytes secrete thrombospondin 1 and thrombospondin 2 (TSP-1 and TSP-2), large, trimeric extracellular matrix proteins that promote the formation of silent synapses in vitro and in vivo (i.e., synapses that are presynaptically active, but postsynaptically silent because they lack functional AMPA-Rs) [100]. TSP1 can bind postsynaptic neuroligins, increasing the speed of excitatory synapse formation at early stages in cultured rat hippocampal neurons, although not the final density of the synapses formed in mature neurons [101]. Hevin, another protein secreted by astrocytes, can modify the interaction between two SAMs in the synaptic cleft by working as an adaptor protein [102]. Hevin binds directly to neurexin 1α and NLGN1(+B), a pair of SAMs that normally do not interact, and engages them in a trans-synaptic bridge promoting excitatory synapse formation [102]. It is thought that the nine-amino-acid splice insert at site B in NLGN1(+B) sterically blocks the interaction between NLGN1 and the sixth LNS domain of neurexin 1α (L6) (refer back to Figure 1 ) thereby forming a key component of the “neurexin-neuroligin splice code,” reviewed in [23]. The bridging of neurexin 1α and NLGN1(+B) by hevin, overriding the splice code, was shown to be critical to form thalamocortical connections in the developing visual cortex in vivo [102]. Therefore, astrocytes by secreting proteins that interact with bona fide SAMs can modify their interactions and regulate protein interactomes in the synaptic cleft.

4.6. Novel Mechanisms to Regulate SAMs

It is likely that additional novel mechanisms exist that regulate SAMs, impacting their function in synaptic activity-dependent ways. One tantalizing mechanism is that SAMs undergo protein structural changes in response to synaptic activity. Perhaps mechanisms will be validated confirming that SAMs can sense synaptic activity in the synaptic cleft and adjust their protein interactions in response via (allo)steric mechanisms. Certainly, incorporation of an alternative splice insert in a SAM in response to synaptic activity (as discussed above) would be one way to induce a protein conformational change. Such a splice insert driven conformational change would have the potential to alter protein interactions within the synaptic cleft. The splice inserts SS#1 and SS#6 in neurexin 1α are of interest in this respect because they integrate into molecular hinges within the neurexin ectodomain and are poised to alter the conformation of domains with respect to one another. However, it is not known yet if these splice inserts are subject to activity-dependent incorporation [74, 103]. A novel protein conformation or interaction site in a SAM might also be induced upon binding of a protein partner and controlled though synaptic activity-induced expression of that partner (refer back to Figures 2(b) and 2(c) ). Neuronal activity-induced expression of α-dystroglycan [40], which binds the L2 domain of neurexin 1α and appears to sterically block the interaction of neurexin 1α with neuroligins via the L6 domain, is a prime example [68] (refer back to Figure 1 ). Synaptic stimulation also appears to induce homodimerization of N-cadherin, an event altering the overall protein architecture [104]. Lastly, the protein conformation of a SAM containing Ca 2+ -binding sites might also be altered by changes in Ca 2+ levels in the synaptic cleft as a result of synaptic activity, affecting its interactions with protein partners. Experimental evidence is accumulating that Ca 2+ levels decrease in the synapse cleft in response to (prolonged) synaptic activity, a result of Ca 2+ flooding into the presynaptic terminal during synaptic vesicle release and/or into the postsynaptic terminal upon NMDA-receptor activation [105, 106]. It has been suggested that the extracellular Ca 2+ -level in the synaptic cleft is

1 mM and can drop significantly, maybe as much as 30�% as presynaptic and postsynaptic channels open [107]. Studies on trans-complexes of cadherins have shown that their interactions depend in part on extracellular Ca 2+ levels and are rapidly decreased when extracellular Ca 2+ is depleted [108]. Thus, additional and novel mechanisms to regulate SAMs in response to synaptic activity may be validated in the near future.

Computer Techniques and Algorithms in Digital Signal Processing

Bryan W. Stiles , Joydeep Ghosh , in Control and Dynamic Systems , 1996

2.1 Habituation

Habituation is perhaps the simplest form of learning. In the absence of an unconditioned stimulus, the response to any conditioned stimulus degrades with each repetition of that conditioned stimulus. In biological neural systems, it has been observed that neurons respond more strongly to stimuli which occur infrequently. If a stimulus occurs often and is not classically conditioned, the neuron loses its ability to respond to that stimulus. Conversely if the stimulus is not observed for a long period of time, the neurons ability to respond may return. Experimenting with Aplysia has clarified the neural basis for habituation [BK85] . Bailey and Kandel showed that habituation was localized at a single synapse. Repeated firing of the presynaptic neuron depressed the strength of the synaptic connection. The postsynaptic neuron, therefore, responded less strongly to any stimulus which activated the presynaptic neuron. This behavior showed both short and long term effects. In the short term, synaptic strength could be caused to decrease quickly and then rebound. Conversely, if the synaptic strength was reduced for a long period of time it required a long period of time to reestablish itself. Short term activation of the presynaptic neuron was found to reduce the influx of Ca 2 + which is necessary for neurotransmitter release. Long term habituation led to long periods of Ca 2 + deprivation which in turn made the electrical connection between neurons immeasurable and caused changes in the physical structure of the synapse.

The Byrne and Gingrich model is based on the flow of neurotransmitter among the external environment and two pools internal to the neuron [BG89] . One of the pools, the releasable pool, contains all the neurotransmitter ready to be released when the neuron is activated. The other pool, the storage pool, contains a store of neurotransmitter for long term use. Short term habituation is explained as the depletion of the releasable pool due to frequent activation of the neuron. The increased level of Ca 2 + which results from the occurrence of the conditioned stimulus increases both the flow from the storage pool to the releasable pool and the release of neurotransmitter. It is the increase in neurotransmitter release which leads to activation of the neuron. In this manner, both pools are depleted by the frequent occurrence of conditioned stimuli. The neurotransmitter in the releasable pool can be replenished by diffusion from the storage pool or by other neurotransmitter flows which are regulated through sensitization and classical conditioning. Long term habituation can be explained by depletion of the storage pool itself. The Byrne and Gingrich model assumes a single flow into the storage pool from the external environment. This flow is proportional to the difference between the current neurotransmitter concentration in the pool and the steady state value.

Another model for both long term and short term habituation was presented by Wang and Arbib and is reproduced as follows with straight forward modifications [WA92] . This model was produced independently from the Byrne model, and is based on Wang and Arbib’s own experimental observations. The modifications introduced here merely change the equations from continuous to discrete time, which is necessary in order to use them later in an artificial neural network. Here I(t) is the current input vector from the neurons whose outputs are habituated, and W(t) is the vector of synaptic strengths. The dependence of W(t) on sensitization or classical conditioning effects is ignored. Since this habituation only version of W(t) is dependent only on the activation of the presynaptic neuron, only the single subscript, i, is needed. Synapses attached to the same presynaptic neuron habituate in the same manner. Henceforth W(t) will be referred to as the habituation value to avoid confusion with either a more complete model of synaptic strength or artificial neural network parameters.

In this model, τi is a constant used to vary the habituation rate and α is a constant used to vary the ratio between the rate of habituation and the rate of recovery from habituation. The function zi(t) monotonically decreases with each activation of the presynaptic neuron. This function is used to model long term habituation. Due to the effect of zi(t) after a large number of activations of the presynaptic neuron the synapse recovers from habituation more slowly. Some assumptions about the range of values for the constants are made in order to assure that Wi(t) and zi(t) remain within the range [0,1]. Specifically, τi, γ, the product of τi,·and α and Ii(t) must all be in the same range [0,1]. For simplicity, Wį(0) will always be assumed to be unity unless otherwise stated.

It is apparent in Wang and Arbib’s model that in the long term, if the presynaptic neuron is not completely inactive the synaptic strength will eventually decay to zero, because zi(t) is monotonically decreasing. This was valid for Wang and Arbib’s research because they were examining the response of animals to artificial stimuli which are of no importance to the animals in question. Sensitization and classical conditioning are ignored in this model. If these other two learning mechanisms were included in the model, then the synaptic strength would only decay to zero in the absence of any unconditioned stimuli.


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