Time to get back to Answering Some Questions. Where I attempt to answer the search-engine questions which have led you to The Cellular Scale. I mainly try to answer questions that I am sure are not answered anywhere on this blog.
1. "What does a cellular cell look like?"
Good question. First of all, what is a cellular cell? Is it different from a regular cell?
Cells look like all sorts of things. Some look like footballs, some look like sea coral. Some cells look like little rafts, drifting down a river.
This is a real true very good question. The strength of the Golgi stain lies precisely in its sparse labeling. If it labeled all cells it would be useless because you wouldn't be able to see the elaborate morphology of a neuron's dendrites.
However, even though it has been around for almost 150 years, it is still unclear why it doesn't stain all cells. It is not clear how it 'decides' to stain one cell and not the one next to it. This is always a bit of a problem for people wanting to use the Golgi stain, because you always have that nagging feeling that maybe you are seeing only the sick neurons or only the neurons with random undiscovered quality X, and so forth. But it is a well respected technique, and journals regularly publish scientific articles which rely on the Golgi stain.
Synapses, the connections between neurons can strengthen and weaken depending on the specific activity at that synapse. This is called synaptic plasticity, and we've talked about it a lot on this blog (here, here, here and here).
the strengthening and weakening of synaptic connections corresponds to the spine growing or shrinking (Matsuzaki 2007)
However, there is another kind of plasticity that can occur at synapses. This is called homeostatic plasticity. And instead of the synapse strengthening or weakening depending on the specific activity at that synapse, the synapses strengthen and weaken in homeostatic plasticity depending on the activity of the whole cell.
To drastically simplify, each cell 'wants' to fire about a certain amount, if it suddenly starts to fire a lot less, it will take steps to strengthen its connections or make itself more 'excitable' so it can get back to its preferred amount of firing. Similarly if the cell starts to fire a lot more than normal, it will take steps to make itself less excitable and to weaken its connections until it reaches the right amount of firing.
A recent paper from the Pak lab explains how in some specific neurons in the hippocampus (CA3 pyramidal cells), the activity of the whole cell is strongly controlled by a some very peculiar synapses. These synapses are close to the cell body, and are on these HUGE weirdly shaped spines (see above) called "Thorny Excrescences". For comparison 'normal' spines look more like this:
The Thorny Excrescences (TEs) are massive spines that contain many separate synapses on them, but connect to the dendrite through 1 neck. 'Normal' spines, on the other hand, usually have 1 synapse at the spine head, and connect to the dendrite through 1 neck.
The size of the TEs, and their proximity to the soma makes them an extremely powerful way to control the signals that the soma receives. Lee et al (2013) shows that when you drastically reduce activity by blocking action potentials (using TTX), you get massive growth of these TEs, but the normal spines further away from the soma stay the same.
They test 3 things to determine whether the TEs have undergone homeostatic plasticity. They look at the morphology (they are bigger), the activity (the electrical signals from them are bigger) and the molecular signatures (the molecules indicative of new synapses are more plentiful). The paper is a really nice complete story showing that these TEs have a lot of control over the general activity of the cell.
It also solves an important problem with homeostatic plasticity. That is, how can the general activity of the cell be modulated without the specific differences between synapses being erased, and consequently the memories or pieces of information they encode? If homeostatic plasticity occurs at spines dedicated to it, then the other spines can still encode specific signals while the activity of the cell as a whole changes.
STORM stands for Stochastic Optical Reconstruction Microscopy. While Array tomography and Serial block-face EM are both revolutionary in that they can combine very high resolution imaging with relatively large volumes of tissue, STORM is an advancement that lets you see tiny tiny little molecules within the cell.
The problem with 'normal' imaging is that molecules are smaller than the diffraction of light.
In the figure above, imaging some tiny molecules next to each other is impossible with traditional fluorescence microscopy, but with STORM, you can resolve 10s of nanometers (nm).
To do this, STORM uses photoswitchable dyes, which means that the dye can be turned on or off. This allows researchers to turn on tiny little areas and then turn them off. If all the dye is turned on all at once, the image will look like a big mess because the signals will all overlap each other. But turning on only a few at a time allows you to estimate where the actual protein or molecule is.
"The imaging process consists of many cycles during which fluorophores
are activated, imaged, and deactivated. In each cycle only a subset of
the fluorescent labels are switched on, such that each of the active
fluorophores is optically resolvable from the rest. This allows the
position of these fluorophores to be determined with nanometer
precision." -Zhuang lab webpage
So what amazing things can they do with this STORM?
A recent paper by Xu et al. (2013) found that the actin which plays a huge role in the intracellular structure of a neuron, has a specific ring-like structure along the axons.
This is the kind of research that will immediately go into neuroscience and cell biology textbooks. Xu et al. discovered how actin was structured along the axon simply by being able to 'see it'.
Not only did they discover the structure of actin and spectrin (magenta above) in the axon, but they also found some other interesting molecular patterns that appear to relate to the actin ring structure. The sodium channels, which control action potential propagation down the axon, are concentrated about half way between the ends of the spectrin tetramers. The potential for super-resolution microscopy like STORM is huge. The location of molecules with relation to one another probably plays a huge role in the function of cells and now we have the tools to map them.
Xu K, Zhong G, & Zhuang X (2013). Actin, spectrin, and associated proteins form a periodic cytoskeletal structure in axons. Science (New York, N.Y.), 339 (6118), 452-6 PMID: 23239625
I am discussing really amazing new techniques to see inside cells this month, and have already posted about the magic that is Array Tomography. Today we'll look at another amazing new technique that (like array tomography) combines nano-scale detail with a scale large enough to see many neurons at once. This technique is called Serial Block-face Electron Microscopy (SBEM), and was recently used to investigate how starburst amacrine cells control the direction-sensitivity of retinal ganglion cells.
SBEM images are acquired by embedding a piece of tissue (like a retina) in some firm substance and slicing it superthin (like 10s of nanometers thick) with a diamond blade. The whole slicing apparatus is set up directly under a scanning electron microscope, so as soon as the blade cuts, an image is taken of the surface remaining. Then another thin slice is shaved off and the next image is taken, and so on.
Using this technique, Briggman et al. (2011) are able to trace individual neurons and their connections for a (relatively) large section of retina. What is so great about this paper is that before they sliced up the retina, they moved bars around in front of it and measured the directional selectivity of a bunch of neurons. Then, using blood vessels and landmarks to orient themselves, they were able to find the exact same cells in the SBEM data and trace them.
The colored circles above represent the cell bodies and the black 'tree' shape are the blood vessel landmarks.
Once they found the cell bodies, the could trace the cells through the stacks of SBEM data. What is really neat is that you can try your hand at this yourself. This exact data set has been turned into a game called EYEWIRE by the Seung lab at MIT.
Reconstructing the cells, they could not only tell which cells connected to which other cells, but they could also see exactly where on the dendrites the cells connected. This is the really amazing part. They found that specific dendritic areas made synapses with specific cells.
Briggman et al. (2011) Fig4: dendrites as the computational unit
This starburst amacrine cell overlaps with many retinal ganglion cells (dotted lines represent the dendritic spread of individual RGCs)...BUT its specific dendrites (left, right, up down etc) synapse selectively onto RGCs sensitive to a particular direction. Each color represents synapses onto a specific direction-sensitivity. e.g. yellow dots are synapses from the amacrine cell onto RGCs which are sensitive to downward motion.
This suggests that each individual dendritic area of these starburst amacrine cells inhibits (probably) a specific type of RGC, and that these dendrites act relatively independently of one another.
"The specificity of each SAC dendritic branch for selecting a
postsynaptic target goes well beyond the notion that neuron A
selectively wires to neuron B, which is all that electrophysiological
measurements can test. Instead the dendrite angle has an additional,
perhaps dominant, role, which is consistent with SAC dendrites acting as independent computational units." -Briggman et al (2011)(discussion)
These cells are weird for so many reasons, but the ability of the dendrites to act so independently of one another is a new and exciting development that I hope to see more research on soon.
Briggman KL, Helmstaedter M, & Denk W (2011). Wiring specificity in the direction-selectivity circuit of the retina. Nature, 471 (7337), 183-8 PMID: 21390125
Salamanders and their amazing leg-growing superpower (source)
Not because they can survive in fire (they can't), but because they can regrow amputated limbs.
A paper in 2007 investigates exactly what neural signals are required for this amazing superpower.
This paper brings together two interesting things about salamander (newt) leg growth.
1. The salamander arm 'knows' where it was cut. If it is cut at the wrist it only grows a hand (paw?...foot?), if it is cut at the shoulder, it grows the whole leg/arm. So one question is HOW does the arm know?
The answer is surprisingly simple: there is a small protein called Prod 1 that is highly concentrated at the shoulder and progressively decreases along the arm. This protein could tell the new bud of growing cells where it is, and what it should grow into.
and
2. To regenerate, the arm needs intact nerve endings at the point of the cut. That is, the nerve fiber that goes down the arm has to be attached to the nervous system. If the nerve is cut further up than the arm cut, the arm will not regenerate.
Kumar et al., 2007 Author Summary Figure
Kumar et al. (2007) found a molecule that ties these two interesting things together, completing the newt leg regeneration story. They find a molecule, nAG (n for newt and AG for anterior gradient) which binds to Prod 1, and is secreted by the nerve sheath (the Schwann cells that surrounds nerve fibers).
They show that when they cut the nerve further up the arm (denervation), they don't get nAG expression and they don't get limb regeneration. But, when they artificially supply nAG, (see D and E above), the amputated and denervated limb starts to grow.
This is a really neat 'rescue experiment' suggesting that the reason the nerve is necessary for regeneration is because it triggers nAG release which binds to Prod 1 and says "GROW".
One thing that they don't do (because genetically manipulating salamanders is not really a thing yet) is remove nAG, but keep the nerve intact. This would show that the only important thing the nerve fiber is doing is triggering nAG.
This study is also a small step towards limb regeneration in humans, not because injecting nAG into an amputated human limb could regenerate it (It couldn't), but because the more we understand about how the system works, the more likely we can figure out a way to engineer a similar system in humans.
Kumar A, Godwin JW, Gates PB, Garza-Garcia AA, & Brockes JP (2007). Molecular basis for the nerve dependence of limb regeneration in an adult vertebrate. Science (New York, N.Y.), 318 (5851), 772-7 PMID: 17975060
Today's post is brought to you by @BabyAttachMode, who is an electrophysiologist and blogger. Today we are blog swapping! I have a post over at her blog and her post about AMPA receptors and LTP is here. So enjoy, and when you're done reading about the newest advances in synaptic plasticity here, you can head over to InBabyAttachMode and read about my personal life. AMPA Receptors are not Necessary for long term potentiation
Science is most
interesting to me when you’re testing a hypothesis, and not only do you prove
the hypothesis to be false, but you discover something unexpected. I think that
happened to Granger et al. They were
trying to find which part of the AMPA receptor is necessary for long-term
potentiation
(LTP), the process that strengthens the connection between two brain cells when
that connection is used often. Indeed they find that AMPA receptors are not necessary at all for LTP, which is very
surprising given the large body of literature describing how the GluA1 subunits
of the AMPA receptor, through interactions with other synaptic molecules that
bind to the intracellular C-tail (the end of the receptor that is located
inside the cell), are inserted into the synapse to induce LTP.
The authors made an
inducible triple knock-out, which means that they could switch off the genes
for the three different AMPA receptor subunits GluA1, GluA2 and GluA3. This
way, they ended up with mice that had no AMPA receptors at all. The authors
were then able to selectively put back one of the AMPA receptors, either the
entire receptor or a mutated receptor. By inserting mutated receptors, for
example a receptor that lacks its intracellular C-tail that was thought to be
important for insertion of the AMPA receptor into the synapse, they could then
study whether this mutated receptor was still sufficient for induction of LTP.
Surprisingly, they
found that deleting the C-tail of the GluA1 subunit does not change the cell’s
ability to induce LTP. Even more so, they showed that you don’t even need any
AMPA receptor to still be able to induce LTP; the kainate receptor (another
type of glutamate receptor that has never been implicated in LTP) can take over
its job too.
Figure 6C from Granger et al. (2013). Kainate receptor overexpression can
lead to LTP expression, without the presence of AMPA receptors.
About this surprising
discovery the authors say the following:
"These results demonstrate the synapse's remarkable flexibility to potentiate with a variety of glutamate receptor subtypes, requiring a fundamental change in our thinking with regard to the core molecular events underlying synaptic plasticity."
Of course if you say something like that, the main players in the LTP field will have something to say about it, and they did. Three giants in the field of synaptic physiology commented in the journal Nature, but their opinions differed. Morgan Shang called it "a step forward", whereas Roberto Malinow and Richard Huganir called it "two steps back", saying that LTP without AMPA receptors can only happen in the artificial system that the authors of the paper use to study this. They expect that cells lacking all three AMPA receptors will look so different from the normal cells that the results are difficult to interpret.
Either way, this paper opens new views and questions to how LTP works, and whether AMPA receptors are as important as we thought.
Granger
AJ, Shi Y, Lu W, Cerpas M, & Nicoll RA (2013). LTP requires a
reserve pool of glutamate receptors independent of subunit type. Nature, 493 (7433), 495-500 PMID: 23235828 Sheng M, Malinow R, & Huganir R (2013). Neuroscience: Strength in numbers. Nature, 493 (7433),482-3 PMID: 23344353
But how, when and why these neurons grow is currently under investigation. A 2008 paper attempts to answer the 'when' of neurogenesis. They labeled (PH3) cells in the mouse hippocampus (dentate gyrus to be specific), and counted how many cells were currently going through mitosis at different times of day. They found that during the dark phase, more cells were PH3-positive, indicating that more cells were growing at night.
They also tested whether neurogenesis was modulated by exercise. And it was. Mice who had access to a running wheel in their cage grew about the same number of cells during the night, but grew more cells during the day. So much so that the difference between night and day disappeared.
This figure shows the light-dark cycle (Zeitgeber time) and the number of 'growing' cells. B shows the pattern for control mice, and D shows the pattern for the running mice. Notice that the y axes are scaled differently.
So exercise helped new cells grow, but without exercise more cells grew during the night time. Now all this use of the phrase 'night time' might make you think that this neural growth is happening during sleep.
After a long night of wheel running, Jasper succumbs to a restful days sleep. (source)
But it's not. Mice are nocturnal. They sleep during the day and are wide awake at night. The paper shows that almost all the running that occurs on the running wheel happens at night. So the enhanced cell growth is happening when the mice are active. Why exercising at night causes cells to grow during the day is interesting, but the authors offer no mechanism for why that might be happening.
Sometimes reading the textbook is just too hard. And sometimes it's much easier just to type your exact homework question into a search engine and find the answer. Before we get started you might want to take a look at Smith and Wren (2010) "What is Plagiarism and how can I avoid it?"
This edition of Let Me Answer Your Questions will address 'homework questions.' As always, you can find previous LMAYQ questions here.
Tough Homework Questions are for the Internet (source)
1. "cells that fire together a) wire together. b) definitely don’t wire together. c) become overheated and die. d) wire with inactive cells."
Ok, student. If you have to turn to the Internet for this multiple choice question, you need a serious lesson in test-taking skills. Here's a tip. If you don't know the answer, eliminate some because they are obviously not the right answer. A good rule to follow is if it says definitely or all or always in the answer it is unlikely that that is the right one. So we can eliminate B. If you know anything about neurons from your class, you should at least know that neurons fire. If they didn't fire they wouldn't 'work'. So you can eliminate C. If all the cells that fired together overheated and died, you would basically not have any neurons left in your brain after reading this sentence. Now you have a 50-50 chance of guessing it correctly. Not too bad. But seriously, if one answer creates a cute little rhyme with the question... it's probably going to be that one. So yes, neurons that fire together wire together.
2. "explain simply where the hippocampus is"
The hippocampus is one of the most famous brain structures because it has to do with encoding new memories. It's name comes from the Greek hippo (horse) and campus (sea), because it looks like a seahorse:
(By the way, potamus=river, so a hippopotamus is a 'river-horse'). Back to the hippocampus: It is a structure in the brain and it is located subcortically meaning under the cortex. Specifically it's located under the temporal lobe of the cortex. There are two of them, one on each side of brain.
3. "Why are neurons and blood cells structured and shaped differently from each other?"
Smith N Jr, & Wren KR (2010). Ethical and legal aspects part 2: plagiarism--"what is it and how do I avoid it?". Journal of perianesthesia nursing : official journal of the American Society of PeriAnesthesia Nurses / American Society of PeriAnesthesia Nurses, 25 (5), 327-30 PMID: 20875892
There are lot of things that fall under the category of "pipette" and I found this a source of much confusion in my early graduate school days. Even after I knew by context what 'hand me the pipette' meant, I had a hell of a time trying to order the right type of pipette from scientific supply companies.
So I am going to do you all a service, and give you a guide to pipette types:
Labeled pipette types (I took this picture)
Basically, things that are long and skinny and can suck up certain amounts of liquid are called pipettes.
Pipet-Aid: I think this is the brand name, but I didn't know what else to call it. It is battery powered and sucks liquid through an electrical vacuum.
Serological pipet: This attaches to the pipet-aid and is calibrated for certain amounts of liquid. We use it for 10-25 mL volumes.
Pipettor/pipette tip: This is the thing that I find most commonly referred to as a 'pipette.' They usually take smaller amounts (from microliters up to 5 milliliters) than the pipet-aid.
Pen: Do not try to use this as a pipette...or a pen. It's more 'cute' than it is 'able to write.'
Large transfer pipettes: These are plastic with squeeze-bulbs at the end. They are not good for precise volumes of liquid like the others so far, but they are a quick easy way to transfer liquid from one place to another. We cut off the tip of the larger kind and use it to gently transfer brain slices into incubation chambers.
Small transfer pipettes: I bought these on accident trying to replenish our supply of large transfer pipettes (#overlyhonestmethods). Now we use them to remove bubbles from the incubation chamber.
Pasteur pipette: These are glass and have detachable squeeze bulbs. I am not really sure what people use them for generally, but we have them in the lab left over from previous experiments. I use them to fill my pH meter with KCl and that's about it.
Micropipette: This is a tiny pipette used for electrophysiology. The tip is so small that you can only see the opening under a relatively powerful microscope. The opening is smaller than the soma of a neuron, and I use these to patch onto brain cells.
So there you have it: the ultimate guide to types of pipettes. I hope that one day this guide will save someone 20 minutes of online searching.
If I missed some kind of pipette, please let me know!
So you already have a neuron, and you've added intrinsic channels to it. The next thing you want to do is add synaptic channels so you can hook this neuron up to other cells.
The main synaptic channels you want to add are the excitatory channels: NMDA and AMPA and the inhibitory channel GABA. These channels don't have the same kind of activation and inactivation
curves and the intrinsic channels do because they aren't activated by
voltage, they are activated by a neurotransmitter.
AMPA and NMDA receptors are activated primarily by glutamate, and cause an influx of sodium and calcium ions. Since both sodium and calcium ions are positively charged, this depolarizes the cell membrane and brings it closer to firing an action potential.
GABA receptors, on the other hand are primarily activated by GABA, and cause and influx of chloride ions into the cell. Because chloride ions are negatively charged, this hyperpolarizes the cell membrane and brings it further away from firing an action potential.
So if you want to have a realistic model of a neuron, you need to add an approximation of these channels. This is easier than adding intrinsic channels, because it is an on/off style (binary) rather than an analogue activation. So basically you just put in the parameters you want like how fast does the channel open and close, how much current does it allow through when activated, and where are they on the neuron.
Of course deciding these parameters is not always easy. A paper out this year in PLoS Computational Biology describes 4 different ways the NMDA receptor can be configured and analyzes the consequences during different stimulation patterns.
The 4 NMDA configurations (based on the 4 different GluN2 subunits) vary in their sensitivity to a magnesium block, how fast they decay, and their maximal current. Above are their responses to the same stimulation patterns (an STDP protocol). Even though they were all receiving the same input pattern, they each show a very different response.
So when considering adding synaptic channels to your model neuron, take the time to find out what the configuration of the receptors should actually be in the type of neuron you are building.
If you are good at following clues, you will realize that I am very, very familiar with this paper.
Evans RC, Morera-Herreras T, Cui Y, Du K, Sheehan T, Kotaleski JH, Venance L, & Blackwell KT (2012). The effects of NMDA subunit composition on calcium influx and spike timing-dependent plasticity in striatal medium spiny neurons. PLoS computational biology, 8 (4) PMID: 22536151
With all the hubbub about the first ever video of an attacking giant squid in the wild about to unveiled, I started wondering about the giant axon of the giant squid... I mean it would be huge right?...
Squid are special creatures to neuroscientists. Specifically to neurophysiologists, who study the electrical activity of neurons.
Squid Axon location
Atlantic squid have this huge (1mm) amazing axon running down each side of their mantle which allowed for the first recordings of action potentials in the 1930s.
Here is a really nice 5 minute video showing how with (by today's standards) very crude techniques, the electrical signal could be recorded from these axons.
So the squid giant axon is neat, and modern neurophysiology would probably not exist with out it. But what about the GIANT squid giant axon? Wouldn't that be an electrophysiologist's dream?
If it scaled proportionally to say, mantle length, the 1foot long Atlantic squid with a 1mm diameter axon would become a 16 foot long GIANT squid with a 16mm giant axon.
Let's think about this for a minute, 16mm is about 5/8 of an inch.
That is like the diameter of a dime! For those not familiar with US coins, it's like the size of a bead on a necklace... a big bead, like a nice-sized pearl. Basically HUGE considering that most axons in vertebrates are not even visible without a microscope.
However,before you all start running out to hunt the giant squid for its precious precious axon...the truth is that the giant squid does not have a super-giant dime-sized axon. The giant squid axon actually has a smaller diameter than the 'normal' squid axon. Surprising right?
Do the giant squid just have more axons there, so they don't need one gigantic one? Or is this axon somehow magically myelinated (probably not)? Or does the giant squid just not need one?
First, let me explain that this information was pretty hard to come by and basically anecdotal. I watched a few dissections of giant squid. And while these were really amazing (look at the hooks on the colossal squid's tentacles!), they said very little about the giant axon or how it was modified in these larger animals.
hooks of the colossal squid tentacles, yikes! (source)
This information comes from a comment quoting JZ Young at a 1977 symposium describing his dissection of a 125cm (about 4 feet) long giant squid. I could not get access to this manuscript, so I have to trust the commenter with his quote:
“Everyone wants to know whether giant squids have giant giant fibres. We
have no material of the central nervous system but some years ago I was
able to dissect the stellate ganglion of an animal washed up at
Scarborough in 1933 and sent to the British Museum. The mantle length
was 125 cm. The nerves of the mantle muscles are arranged in this genus
differently from any other I have seen. Those in the front part of the
mantle arise from a relatively small stellate ganglion, in the usual
way. The hinder part of the mantle, perhaps more than half of the whole,
is suspended from a distinct median nerve, running with the fin nerve
and giving off a series of branches to the mantle.
Each of the nerves arising from the ganglion contains one or two large
fibres, ranging in diameter from about 80 micrometers in the more
anterior ones to a maximum of 250 micrometers further back. The median
nerve was further preserved but one fibre of about 250 micrometers could
be seen. Two of the more posterior branches contained fibres of about
200 micrometers each. None of the nerves examined contained the
exceptionally large fibres reported by Aldrich & Brown (1967). We
may conclude that Architeuthis is not an especially fast-moving animal.
This would agree with evidence that it is neutrally buoyant with a high
concentration of ammonium ions in the mantle and arms (Denton, 1974).”
Young explains that the axon network is set up differently in the giant squid (Architeuthis). He reasons that because the axon is not especially large, it could only conduct so fast, and therefore the fast escape reflex which it causes in the normal squid is just not that fast in the giant squid. This sort of makes sense, in that the giant squid might not benefit from escape as much as the normal squid. The giant squid might be better served by having razor sharp teeth on its suckers or terrifying pain causing-hooks so it could fight away a predator.
The biggest axon award goes to the Humboldt Squid which has an axon the 'size of spaghetti.'
Kubodera T, & Mori K (2005). First-ever observations of a live giant squid in the wild. Proceedings. Biological sciences / The Royal Society, 272 (1581), 2583-6 PMID: 16321779
JZ Young, 1977 The Biology of Cephalopods Symposia of the Zoological Society of London #38
There are two aspects to neuron shape. One is the pattern of dendritic or axonal branching, and the other is the pattern of spines. Spines are the little protrusions that come off of the dendrite often receiving synaptic inputs.
Because these spines are associated with excitatory synapses, and because synapse development is thought to be the cellular basis of learning, it makes sense that spines would grow when we learn.
But how would they grow exactly?
Using transcranial two-photon microscopy (a window into the brain of a living mouse), Fu et al. (2012) have caught images of neural learning in action.
The authors used two learning tasks to investigate how spines grow during learning. In the "reaching" task, mice had to reach their paw into a slit and grab a seed. In the "capellini handling task" the mouse is given a 2.5 cm length of (I am not making this up) angel hair pasta and learns how to handle it for eating. learning is measured by how fast the mouse eats the pasta.
learning how to eat pasta makes mouse cortical spines grow (source)
They found that spines grow during learning (not too surprising). But spines also grow when the mouse is exposed to a motor-enriched environment (like a mouse-sized playground).
The interesting difference between learning a specific task rather than just playing is that the spines grow in distinct clusters when the mice are taught a learning task. C shows the total spine growth, while D shows the proportion of clustered spines to total spines. Reach only means the mice were only taught the reaching task, and cross-training means they were taught both the reaching task and the pasta handling task.
The authors explain two possible functions for these spine clusters:
"Positioning multiple synapses between a pair of neurons in close
proximity allows nonlinear summation of synaptic strength, and
potentially increases the dynamic range of synaptic transmission well
beyond what can be achieved by random positioning of the same number of
synapses."
Meaning spines that are clustered and receive inputs from the same neuron have more power to influence the cell than spines further apart.
"Alternatively, clustered new spines may synapse with distinct (but presumably functionally related) presynaptic partners.
In this case, they could potentially integrate inputs from different
neurons nonlinearly and increase the circuit’s computational power. "
Meaning that maybe the spines don't receive input from the same neuron, but are clustered so they can integrate signals across neurons more powerfully.
And of course...
"Distinguishing between these two possibilities would probably require circuit reconstruction by electron microscopy following in vivo imaging to reveal the identities of presynaptic partners of newly formed spines."
More work is needed to figure out what is really going on.
Fu M, Yu X, Lu J, & Zuo Y (2012). Repetitive motor learning induces coordinated formation of clustered dendritic spines in vivo. Nature, 483 (7387), 92-5 PMID: 22343892
A recent paper from France details the making of a 3D environment that can facilitate 'realistic' neural growth. Labour et al. (2012) created a collagen biomimetic matrix which contains neural growth factor (NGF).
These scanning electron microscope images show the porous fibril texture of the collagen matrix. Most of the paper is spent explaining the methods for making this biomimetic matrix, but they also actually grow some pseudo-neurons (PC-12 cells) on the matrix.
They show that when cultured on top of this collagen surface, the cells extend neurons in three dimensions into the matrices and are affected by the NGF. (when there is no NGF, the neurites don't grow and the cells die.)
This paper is mostly about the methods, but I like the new possibilities that growing 3D cells opens up. With these biomimetic collagen matrices, the factors that cause specific dendritic arborizations in three dimensions can be analyzed. The environment can be completely controlled and the neurons easily visualized during growth. The authors suggest using these matrices to study neurodegeneration as well.
Another interesting thing this paper introduced me to is the 'graphical abstract.' I didn't know that that was a thing, but it seems like a good idea. However, trying to summarize an entire paper in one figure seems pretty difficult. Here is their attempt:
Labour et al. (2012) graphical abstract
I think it does actually get the feel of the paper across pretty well, though it's not really informative without the actual abstract next to it.
Labour MN, Banc A, Tourrette A, Cunin F, Verdier JM, Devoisselle JM, Marcilhac A, & Belamie E (2012). Thick collagen-based 3D matrices including growth factors to induce neurite outgrowth. Acta biomaterialia, 8 (9), 3302-12 PMID: 22617741
