LMAYQ: Let me do your homework for you

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: Hippocampus = Seahorse (source) (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?" Neuron and Blood cell Knitting (by Estonia76) This is a great question, but it has the ring of 'I need help with my homework' about it. I talk a lot about the shapes of neurons in this blog, usually speculating on why different neurons would be shaped differently from each other. But this is a good question, why do neurons have dendrites and axons in the first place? Well basically neurons need to receive and transfer information, while blood cells need to physically move to transfer oxygen. Neurons stay in place, while blood cells travel all over the body. Blood cells need to be small and hydrodynamic to float through your blood vessels. Neurons need to 'cover space' to contact many other neurons, so they have branching dendrites and axons. © TheCellularScale 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

A cellular 2012

It's been an exciting first year of blogging here at The Cellular Scale.

Glowing Neuron

Let's take a look back at the Cellular year, shall we?

I am going to do this two ways: Today I'll post the first sentence of the first post of each month from this blog as is a blogging tradition. Next post, I'll list my personal favorite posts from each month.

January: "Hello and welcome to The Cellular Scale."

February: "Food smells better when you're hungry, right?"

March: "Another adventure out side the "cellular neuroscience" walls for The Cellular Scale."

April: "I love reading other blog posts about ridiculous scientific (and unscientific) claims."

May: "How do you build a virtual environment for a worm?"

June: "Andrew Huxley is one of the founders of both modern electrophysiology and  computational neuroscience, and is consequently a personal hero of mine."

July: "...toward preventing PTSD symptoms."

August: "Zebra finches are a popular model for language learning because unlike most research animals which may have instinctual vocalizations, zebra finches (the male ones at least) learn their signature song from experience."

September: "I have always believed that scientific research is another domain where a form of optimism is essential to success: I have yet to meet a successful scientist who lacks the ability to exaggerate the importance of what he or she is doing, and I believe that someone who lacks a delusional sense of significance will wilt in the face of repeated experiences of multiple small failures and rare successes, the fate of most researchers"     -Daniel Kahneman

October: "It's about to get really neuro-heavy here at The Cellular Scale because of the impending Society for Neuroscience annual conference."

November: "Time to get back to Answering Your Questions."

December: "Seriously."


© TheCellularScale

Cortical spine growth and learning how to eat pasta

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.

spines on a pyramidal neuron (source)

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.

A window into the mouse brain (source)

 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).

Fu et al. 2012 (Figure 2C+D)

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.

 © TheCellularScale


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

Can you turn a rat gay?

What does it take to 'turn a rat gay'? This question may have crossed your mind, but a group in Mexico actually did the experiments to test it.

A weak first attempt (source)

Triana-Del Rio et al., 2011 used a co-habitation conditioning paradigm to see if they could condition a male rat to prefer a male partner.
The basic paradigm was to house the 'experimental rat' to the 'stimulus rat' (who was scented with almond) for a full day every 4 days. Under these conditions, the experimental rat did not show any preference for the almond-scented stimulus rat later on.  However, if the experimental rat was injected with quinpirole, which stimulates dopamine D2 receptors, he did develop a preference for the almond-scented rat. This preference was not sexual in nature. Preference was measured by time spent together, and these guys just wanted to hang out.

Triana-Del Rio et al., 2011 (figure 1)

The authors then did a separate experiment where instead of using 'sexually naive' rats as the stimulus rats, they used 'sexually expert' rats.  They created these Cassanovas by riling them up with very 'receptive' female rats at least 10 separate times. They refer to this as 'sexual training.' When the sexually expert rats were used as stimulus rats, the experimental rats developed a sexual preference when injected with quinpirole. These experimental rats strongly preferred their almond-scented partners as measured by time spent together, mounting, and 'genital investigation.'

So what does this mean? First of all, even the most drastic change was not permanent, partner preference dissipated after 45 days. And as I mentioned in my SfN summary, this protocol did not have the same effect in female rats. I do not think that the researchers here 'turned a rat gay.' While they did succeed in biasing the preference of the experimental rat for the guy he was housed with, they certainly didn't change the rats sexual preference in a deep or universal way. There is no evidence that the experimental rat preferred males in general over females, just that he really likes the one guy he was hanging out with.

So this study does not really tell us anything about the biological basis of homosexuality, and it certainly does not tell us how to make a gay bomb. The most interesting implication for this study is in the activity of the D2 dopamine receptor, which may be involved in pair-bonding. I would be interested to see what some ex vivo cellular studies revealed about this treatment. Does quinpirole application cause a change in the number or location of the D2 dopamine receptors or the activity of the neuron?


© TheCellularScale


Triana-Del Rio R, Montero-Domínguez F, Cibrian-Llanderal T, Tecamachaltzi-Silvaran MB, Garcia LI, Manzo J, Hernandez ME, & Coria-Avila GA (2011). Same-sex cohabitation under the effects of quinpirole induces a conditioned socio-sexual partner preference in males, but not in female rats. Pharmacology, biochemistry, and behavior, 99 (4), 604-13 PMID: 21704064
 

SfN Neuroblogging 2012: The Recovery Period

SfN 2012 is finally over, and now I can get back to answering your questions and teaching you how to build a neuron. Things will simmer down and neuroscientists will go back to their research and smaller more specialized conferences. Until May that is, when abstracts of SfN 2013 will be due!

SfN 2013 in San Diego, CA

Here are just a few final tips to cope with the post-SfN feeling.

1. Sleep. Consolidate all that knowledge and decompress. 

2. Consolidate your notes.  Do this right away or else you will completely forget where all those little scraps of paper went with scribbled citations and email addresses. Put them all in one notebook or type them up.

3. Email those people. Whoever they are, you probably got someones email address and told them you would be in contact. Maybe to send them the PDF of your poster, or maybe to get theirs.  Maybe because you had an ACSF recipe to send them, or they were going to tell you the super-secret voodoo chant that they do to get their in situ hybridizations to work every time.  Whatever it was, email them right now. Don't lollygag on this. You might forget to email, or they might forget who you are.

4. Do your receipts. If you are lucky enough to have your conference trip paid for, get all the reimbursement stuff together right away. Some universities (mine included) require that you get all this in order and turned in within a week of returning from the conference.

5. Make use of your motivation. You hopefully came back from SfN full of ideas! Use that excitement: set things up to start that new experiment. Order that new reagent. Write out that new idea for a grant proposal. Read those new papers you hadn't heard of before.

© TheCellularScale

SfN Neuroblogging 2012: Preparation

So you are going to a big scientific conference, congratulations!

Maybe you are going for the very first time and not presenting anything.  Maybe you are presenting your very own first author poster for the first time.  Maybe you are presenting yet another small update in your ongoing project. Maybe you are presenting a nanosymposiom or minisymposium talk. Maybe you are a PI and have a whole labs worth of posters presented by your students and post-docs. 

Whatever your situation, you need to do some preparation. 


for N00Bs:

If you are just attending the meeting, but not presenting anything, you need to do some pre-planning to get the most out of the conference. We are basically talking about the Society for Neuroscience annual meeting here.  And this conference is HUGE.

There are a ton of presentations and you literally cannot see them all (probably not even a quarter of them). So you have to do some preparation.  You can use the SfN meeting planner to search for topics you want to read about and to make an itinerary. You can also use the Hubbian app (http://hacksfn.org/) to browse abstracts and plan your SfN schedule. 

The absolute worst way to 'do SfN' is to just walk through the posters stopping at whichever ones catch your eye. You will miss the ones you are interested in, and will waste a lot of time.


for the poster presenter:

So you are presenting a poster. You are probably (hopefully)  finished or almost finished creating it at this point in time. If you are still working out the layout, you might want to check out Dr. Zen's blog Better Posters. It gives some helpful insights into those important questions like 'what font should I use?' and 'where should my acknowledgements go?'

Now after your poster is made, you will want to practice actually presenting it.  You can do this alone, just going through the explanation of what you did and why you did it. Or you can present the poster to an actual person. This is a better option because then you can get some feedback and practice answering their questions. But no matter what, PRACTICE your poster presentation.

You took so much time and effort to collect the data, run the simulations, analyze everything and layout out your poster. But all that work will be basically for nothing if you can't quickly and concisely communicate your results. You don't want 'Dr. Big Shot' leaving your poster confused and irritated because she couldn't understand the jumble of words you were throwing at her. 


for those presenting a talk:

It's more obvious to people that they need to practice a talk than that they need to practice the poster presentation. But there are a lot of bad presentations out there, and there is a lot of good advice online. I have proposed one single golden rule for presentations, but others have gone into much greater detail. I highly recommend Scicurious's "And Now, A Powerpoint Presentation" for some excellent tips on presenting scientific findings at a conference. 


For the lab head: (PI):

Not being a PI myself, I turned to twitter, asking 'What is the main role for a PI at a scientific conference?'

It basically came down to:

1. Communicate your research as a whole, as in: "Tell your lab's science story" (@Oldsjames) or "talk up lab work" (@GertyZ)

2. Networking, as in: "being the honey bee in the pollen-rich garden" (@neuropolarbear)

3. Help your students out, as in: "Introducing peeps to folks" (@GertyZ) or "pay for lab dinner" (@jsnsndr)

You also might want to take a stroll down 'NIH row' to do some schmoozing as recommended by Drugmonkey. 

So there you have it, tips for SfN attendees at all levels. Now go prepare, people!

© TheCellularScale

Almost Creating a Fake Memory Trace

Mouse Memories (source)

Last post, we talked about the fallibility of flashbulb memories. Today we're going to discuss a new paper in which scientists claim to have created a fake memory in a mouse. 

Garner et al., (2012) use the same kind of genetic trickery that Han et al. (2009) used to erase memories.  They genetically modified mice to express a foreign receptor that mice don't normally express. These kinds of receptors are called DREADDs which stands for "Designer Receptor Exclusively Activated by a Designer Drug." A DREADD can activate the cell, inactivate the cell, or even kill the cell. (Han et al., added a receptor that killed the the cells, but Garner et al. add a receptor than activates the cells.)

But, here's the real genetic trickery, the DREADD is promoted only in the cells that are active at a certain time. When something happens, the cells that are active during the event will express the DREADD. So later, when the designer drug is applied, only the cells which were active during the event will respond.

Using this DREADD system, Garner et al. try to trick mice into thinking that they were shocked in one room, when really they were shocked in another room.  They call this a 'generating a synthetic memory trace' and this is how they do it:

Garner et al., 2012 Figure 2A

First of all the kind of memory the authors are synthesizing is the association between a room (or context) and an electric shock. If you put a mouse in a room and then give it an electric shock, the next time it is in that same room it will 'remember' that that room is scary and will show a freezing behavior. The measurement of how good this memory is is simply counting the percent of the time that the mouse spends freezing in the room.

They have two rooms, context A (Ctx A) and context B (Ctx B).  First they take the mouse and put it in context A (but don't give it an electric shock).  This activates a certain subset of neurons and so the DREADD will get expressed in those neurons. Let's call them the "Context A neurons." Then they stop the creation of new DREADDs by adding in doxycyclin, which turns off the DREADD gene expression. This makes it so (in theory) the only cells that have DREADDs are the "Context A neurons." 

Then they put the mouse in context B, but at the same time they apply the "designer drug" to activate the DREADDs.  Since the DREADDs are (supposedly) only in the "Context A neurons," the neurons that the drug activates should trick the mouse into thinking it is actually in context A, when really it is in context B. Then they apply the shock to the mouse.

To see if they have 'generated a synthetic memory trace' the authors test whether the mouse freezes in context A (where it thinks it was shocked) or context B (where it was actually shocked). 

Garner et al., 2012 Figure 2B&C

Unfortunately the authors don't find something simple.  First of all, they find that the mice with the DREADDs (the filled black circles above) almost always freeze less than the normal control mice (grey triangles), and they don't really explain why that might be. Second of all, they find that the application of the designer drug (+CNO) increases freezing for the DREADD mice in both context A and context B. 

The mouse didn't learn that Context A is where it got shocked.  Instead it learned that Context B with the "Context A neurons" is where it got shocked.  It's like the "Context A neurons" become part of context B. 

The authors call this a 'hybrid memory trace' where the mouse learns to associate a combination of the "Context A neurons" and the actual context B environment with the shock.

So what if just adding this drug is enough to create a hybrid memory? The authors did a nice control experiment to test this. They did the exact same protocol, but put the mouse in context B every single time (never in context A). That way the neurons expressing the DREADD are the "Context B neurons" and should basically be the same set of neurons that are active anyway when the mouse is shocked in Context B. In this case, the mouse froze a lot to context B without the drug, and it froze the same amount to context B with the drug.  The drug caused no enhancement when it was activating the "Context B neurons." This is strong evidence that the hybrid memory trace has to involve the activation of a new set of neurons.

This is a really nice experimental design, but I think that the authors oversold their result a little bit in the title "Generation of a Synthetic Memory Trace." They didn't create a totally fake memory, they created a hybrid memory by adding in new neurons to the 'context' that the animal associated with the shock.  There is no evidence that  the mouse thought it was in context A or even that having a context A is important. If they had just stimulated a random, but new, set of neurons in context B and then stimulated that same random set of neurons when testing the mouse for freezing behavior, they might have seen the same results.

© TheCellularScale


Garner AR, Rowland DC, Hwang SY, Baumgaertel K, Roth BL, Kentros C, & Mayford M (2012). Generation of a synthetic memory trace. Science (New York, N.Y.), 335 (6075), 1513-6 PMID: 22442487

you can't trust your brain: memory

"Flashbulb" memories are those vivid memories of specific salient events.  The 'everyone remembers exactly where they were when...' sort of events.  In the USA, and depending on how old you are, you might remember the assassination of JFK, or Martin Luther King Jr. in this way. In this century, most Americans remember exactly where they were when they heard about the 9/11 attacks on the world trade center and pentagon.

"Never Forget" (source)

It's widely acknowledged these days that the brain is not really a safe place to store information. Memories of events change over time. But for a while the "flashbulb" memory was thought to be immune from the memory-altering properties of time. Think about your own memories of 9/11 or another highly meaningful event. I bet you are pretty certain about the details. I, for example, was in my second year of college and I know exactly who told me that the first tower was hit, exactly where I was standing on the quad, and exactly what class I was going to....

...or do I? 

A study in 2003 tested the consistency of flashbulb memories over time and compared the details to 'control memories' of everyday events. They specifically recorded memories from people during the day after the 9/11 attacks, and then recorded memories of the same events from subsets of those same people 1 week, 6 weeks, and 32 weeks later. They found that the flashbulb memories did have different properties when compared to control memories, but that consistency was not one of them. 

Talarico and Rubin 2003, Figure 1a

Talarico and Rubin show that the flashbulb memories and the everyday memories had the same time-dependent decay (that x axis is in days), demonstrating that the flashbulb memory did not have some special property that protected it from corruption. 

However, they did find that the level of confidence in the memory was higher for flashbulb memories than for everyday memories. People thought (incorrectly) that their memories of the 9/11 attacks were more accurate than their other memories. 

So again we learn the lesson that we cannot trust ourselves.

In the authors words:

"The true 'mystery,' then, is not why flashbulb memories are so accurate for so long,... but why people are so confident in the accuracy of their flashbulb memories." Talarico and Rubin (2003)

But I think the most interesting finding in this paper was that the flashbulb memories of 9/11 were more likely to be recalled 'through ones own eyes' than the everyday memories. Everyday memories were seen 'through ones own eyes' at the beginning and a at 1 week, but at 6 and 32 weeks the everyday memories were more likely to be seen 'from an outside observer perspective.' The flashbulb memories, on the other hand, were seen 'through ones own eyes' at all time points. Indeed, when I think of my own 9/11 memory, I still see it through my own eyes.

The authors don't go into why that might be or what it might mean, so we are left to wonder.

© TheCellularScale



Talarico JM, & Rubin DC (2003). Confidence, not consistency, characterizes flashbulb memories. Psychological science, 14 (5), 455-61 PMID: 12930476

The effect of familiar male voices on neurons

male zebra finch trying to impress female (Max-Planck)

Zebra finches are a popular model for language learning because unlike most research animals which may have instinctual vocalizations, zebra finches (the male ones at least) learn their signature song from experience.

The importance of social experience in male song learning is clear, but what about the effect of social experience on the female response to the male voice?

Menardy et al., 2012 (figure 2C)

Menardy et al., (2012) have recently analyzed the neural response in females to the male distance calls (not songs).  They tested the  response in anesthetized birds, but also in awake, alert birds. To do so, they used a nifty little recording device that they mounted on the back of the females.


They tested the response of the neurons in the caudomedial nidopallium (NCM) to the calls of the female's mate (4 months spent together), a non-mate familiar male (3 days spent together), and an unfamiliar male (complete stranger).

In general, the neurons in the female NCM responded more strongly to the calls of the males that they knew than to the stranger's call. 

Menardy et al., 2012 (figure 5A)

So why is this and what does it mean? The authors point out that this change in neural response could be a result of extensive social interactions (the female bird spent some quality time with the mate and the familiar male), or it could be a result of having heard the call before. 

In other words, Is the NCM encoding a recognition signal ('ah, that's Nick's voice') or a familiarity signal ('I've heard this sound before')?

It is likely that some form of neuroplasticity is taking place during the male-female interactions, but the mechanisms and the meaning behind it are not clear yet. Some interesting experiments might be to test the effect of traditional 'learning disruptors' (such as protein synthesis inhibitors) on this neural preference for familiarity. 

© TheCellularScale


Menardy F, Touiki K, Dutrieux G, Bozon B, Vignal C, Mathevon N, & Del Negro C (2012). Social experience affects neuronal responses to male calls in adult female zebra finches. The European journal of neuroscience, 35 (8), 1322-36 PMID: 22512260

The shape of a memory

Luna Moth (Source)

If an animal changes shape, do its memories change shape as well?
Blackiston et al., (2008) from Georgetown University designed an experiment to test exactly that question.

They exposed caterpillars to a specific smell and then gave them an electric shock. They then tested the caterpillar's aversion to the smell by letting it run around in a Y shaped structure.  One arm had the 'scary smell' and the other just had normal air.

Blackiston et al. 2008 figure 1

After the caterpillars had learned that the smell predicted an electric shock, they preferred the ambient air arm compared to the 'scary smell' arm. Specifically 78% of the caterpillars spent more time in the ambient air arm. 


So, great, caterpillars can learn to avoid a smell.  Not super exciting on its own.  The real test was to train the creature as a caterpillar and then test the creature as a moth.

And indeed, the moths remembered.  80% of adult moths chose the ambient air over the 'scary smell' air.  Interestingly, the moths only remembered if they were trained late in their caterpillar life, but not if they were trained as very young caterpillars.

So what does this mean? Well, like most fascinating scientific findings, it raises many questions.  In particular it makes me wonder what exactly is happening in the brain during metamorphosis?
Are the neurons even firing? Do they go into some kind of paused-frozen state?

I haven't heard of anyone recording the electrical signals from neurons or imaging the calcium dynamics of pupal moths or butterflies, but I think this would be a great experiment.

Clearly the caterpillar isn't completely destroyed and rebuilt, some components persist. The specific synaptic connections that encode the connection between the smell and the scariness must be maintained.

Metamorphosis (source)

And of course this answers the longstanding literary question of how exactly Gregor Samsa can remember who he is after he transforms into a cockroach.

© TheCellularScale


Blackiston DJ, Silva Casey E, & Weiss MR (2008). Retention of memory through metamorphosis: can a moth remember what it learned as a caterpillar? PloS one, 3 (3) PMID: 18320055

A Pain in the Hippocampus

Neuropathic Pain (source)

Pain is usually a helpful sign that something is wrong with a part of your body. Heat-pain will cause you to pull your hand back from something hot before it burns you. The pain of a cut will draw your attention to it, so you can clean it.

However damage to the central or peripheral nervous system can result in chronic neuropathic pain, which is not helpful form of pain. Neuropathic pain is basically some mis-firing or mis-connected pain neurons sending meaningless, but persistant pain signals to the brain. And as bad as that sounds, chronic pain can also apparantly wreak havoc on your brain.

A recent study by Mutso et al., (2012) shows that in both humans and experimental animals, the brain is actually re-organized in response to chronic pain.  Specifically, they look at pain-related changes in the hippocampus, the part of the brain most strongly implicated in memory encoding. 

They compared human patients with chronic back pain, complex regional pain syndrome, and osteoarthritis to people with no pain-related condition, and found that the people with both chronic back pain and with complex regional pain syndrome both had reduced hippocampal volume when compared with the normal control group. The osteoarthritis patients showed a trend toward reduced hippocampal volume, but the result was not statistically significant. 

Hippocampus (source)

So what does this mean? If you have chronic pain you have a smaller hippocampus? We've covered this kind of study before, basketball players had larger striatums that non-basketball players, but it is never really clear what the volume of a brain region tells us. 

Does the volume of a brain structure mean more neurons, more blood flow to that region, more glia cells, or differently shaped neurons?

It is very difficult to draw any conclusions about the effect of pain on the hippocampus simply by learning that the hippocampi of people with chronic pain are smaller than the hippocampi of normal people. 

Luckily the study did not end there. Mutso et al. also investigated the effects of chronic pain on the cellular level. 

Hippocampal Neurons (source)

They found that in mice with chronic pain, the hippocampus has fewer 'new' cells. By staining for two specific markers DCX and BrdU, you can tell which neurons are new.  The hippocampi of control (normal) mice had around 40 new cells, while the chronic pain mice had only 14.  This is an indication that neurogenesis is much reduced in response to chronic pain, and suggests that the reduction in hippocampal volume could be related to fewer new neurons being generated (though it does not show this conclusively).

Unfortunately, chronic pain is bad for your hippocampus, and a cure for both the pain and the collateral brain re-organization are still illusive. 

© TheCellularScale


Mutso AA, Radzicki D, Baliki MN, Huang L, Banisadr G, Centeno MV, Radulovic J, Martina M, Miller RJ, & Apkarian AV (2012). Abnormalities in hippocampal functioning with persistent pain. The Journal of neuroscience : the official journal of the Society for Neuroscience, 32 (17), 5747-56 PMID: 22539837

Neuron-controlled robots: reverse-cyborgs

Last post we discussed robotically controlled biology.  In this post we will talk about biologically controlled robots.

The Hybrot: a rat neuron controlled robot

In 2001, S. Potter published a paper on the "Animat". A set of cultured neurons on a multi-electrode array (MEA, purple circle in above image) interfaced with a simulated robot.  That is, not a physical moving around robot as pictured above, but a computer program simulating what a robot/animal could do. 

They made a virtual room for the animat to 'explore'. (If you can make a virtual environment for a worm, I suppose you can make one for a petri dish of cultured neurons) The signal from the cultured neurons determined where the animat went. If one group of neurons fired, the animat moved left, if another group fired it moved forward, and so forth. (The actual equations translating neuronal activity to animat movement were more complex than this, but you get the idea.) 

So here's the really cool thing: When the animat 'hit a wall', a set of neurons were stimulated with an electric pulse. They also gave the cultured neurons a sort of vestibular system, stimulating a different area depending on which direction the Animat was traveling.

Although this Animat study was using a simulated environment and a simulated robot, using cultured neurons to control an actual robot was only a matter of time. 





Neurons are somehow even cooler when they are combined with robots, no?

So what I think is really exciting about this reverse-cyborg system is that you can study the formation of neuronal networks in response to realistic experience. The feedback system used in the Animat could reveal how natural synaptic plasticity and other network-forming processes could organize a set of neurons. I am particularly interested in the effects of neuromodulation on these neurons.  If they form a certain kind of network under normal conditions, how would that change if they were bathed in dopamine during the 'experience' or serotonin, or whatever. (Pick your favorite neurotransmitter).

It is easy to think that this robot has a 'brain' but really the cultured neurons are not organized like the brain at all.  Watching a network form in a dish is fascinating and can yield information about how neural networks form in general, but don't assume that this will tell us how networks actually form in an actual brain. 

Robots sure are cute (source)

These methods can be used to discover really interesting things about neurons and networks, but other kinds of study (such as ones using real, intact brains) are need to find out what actually happens.

© TheCellularScale


Demarse TB, Wagenaar DA, Blau AW, & Potter SM (2001). The Neurally Controlled Animat: Biological Brains Acting with Simulated Bodies. Autonomous robots, 11 (3), 305-310 PMID: 18584059

Virtual Reality for Worms

How do you build a virtual environment for a worm?


The Nematode C. Elegans with glowing neurons (source)

Using a little optogenetic trickery, you can directly activate specific worm neurons with light.  If you know your worm neurons, you can stimulate ones that make it think it has suddenly touched something with its nose or that the environment is suddenly very salty. 

Before we dive into worm VR, let's back up and discuss this specific worm.

The Magnificent C. Elegans
C. Elegans is a surprisingly popular subject of study in neuroscience. It has a simple and well defined nervous system that contains only 302 neurons (in the hermaphrodite, the rare males have a few extra neurons).  All the neurons and even all the connections between the neurons have been pretty well characterized.  They are small (hundreds can fit on a standard sized petri dish) and they reproduce quickly.  And it that wasn't enough to make C. elegans a desirable subject for study, they can be genetically altered with relative ease, and exhibit rudimentary learning skills. 

A recent technological development has made clever use of genetic tools that allow calcium influx (an indicator of neural activity) to be visualized in neurons and allow neurons to be activated by light.
Faumont et al., (2011) have created a worm tracking system that uses the fluorescence from a genetically altered neuron to locate the worm and recenter the microscope on the worm in real time. This allows for completely non-invasive visualization of neuronal calcium/activity in the awake behaving animal. 

The recent paper in PLoS One, describes exactly how they got the microscope to track the worm in real time without blurring of the signal or messing up the calcium imaging. The paper is open access, so you can go read the details for free.

To see this larger and more clearly, you can download this video and their 4 other supplementary videos here. 
In this video, you can see the animal moving around in the top left, the path it follows in the top right, the calcium fluorescence signal in the bottom left (notice the calcium neuron is always in the field of view), and the activity of this particular neuron when the worm is traveling either forward (blue) or backward (red). 

The "Dedicated Circuit" Hypothesis
The neuron imaged in this video is called AVB, and it is a 'command neuron'.  Faumont et al. show that it increases in activity when the worm is moving forward and decreases when the worm moves backwards.  A similar command neuron, AVA, does just the opposite, increasing when the worm moves backward and decreasing when it moves forward.  These data support what is called the "dedicated circuit hypothesis" which says that the worm uses one set of neurons to go forward and a completely different set of neurons to move backwards.

While Faumont et al. shows that the dedicated circuit hypothesis is supported for command neurons, they find that the activity of the actual motor neurons (the neurons on the body wall that control contraction of the muscles) does not support this hypothesis.  If the dedicated circuit hypothesis was true, the A-type motor neurons should only be active and oscillating during backward movement, and the B-type motor neurons should only be active during forward movement.  They found that this wasn't true, that both were active and oscillating during both forward and backward motion. 

Virtual Reality for Worms
Now back to virtual reality.  This Faumont et al. paper is a showcase of new tools that can be used to study C. Elegans in a simultaneously macroscopic and microscopic way.  One of the new techniques the introduce is the optogenetic stimulation of specific neurons in specific places to create and 'environment' for the worm. 

Faumont et al., 2011 Figure 2

When they genetically express channel rhodopsin, the channel which activates neurons when exposed to blue light in the ASH neuron (a neuron sensitive to osmolarity, or saltiness, changes), they can activate that neuron whenever they want by turning on the blue light.  They create a virtual environment by tracking the worm as it travels in a field, and activating the blue light when it reaches a certain xy coordinate.  In the figure above they activate the neuron when the worm's nose is within the outer ring (traces turn blue).  This makes the worm 'think' that the ring is full of saltier liquid than the rest of the area. 

This virtual environment takes away all the technical difficulties of actually creating a ring of salty water in a pool of less salty water, and the VR environment can be quickly and easily changed into any shape or size, when desired. 
This new tracking method, in combination with calcium imaging and optogenetics, represents a leap forward in cellular scale neuroscience, to non-invasively visualize neuronal activity, activate neurons, and record the coinciding behavior is a combination mammalian neuroscientists can only dream about.

Note: there are ways to image calcium in the neurons of moving mice, but even this requires installing a 'window' into the skull and mounting a mini-microscope on the mouse's head. In addition, the neurons visualized are limited to the ones closest to the surface of the brain.
© TheCellularScale


Faumont S, Rondeau G, Thiele TR, Lawton KJ, McCormick KE, Sottile M, Griesbeck O, Heckscher ES, Roberts WM, Doe CQ, & Lockery SR (2011). An image-free opto-mechanical system for creating virtual environments and imaging neuronal activity in freely moving Caenorhabditis elegans. PloS one, 6 (9) PMID: 21969859

Erasing Memories Cell by Cell

3d glass brain
by Kazuhiko Nakamura

We've discussed recent findings about erasing fears from memories, but today we'll be talking about erasing the fear memory itself. This involves actually inhibiting or killing the individual neurons that encode for a particular memory, so for obvious reasons these experiments are done on mice rather than humans. 

Mice can be trained to associate a mild electrical foot shock with a tone.  The tone plays and then a foot shock is given.  Once the mouse has learned this association, it will freeze in place when the tone is played.  This is called an auditory fear memory. 
Using a fear memory paradigm, Sheena Josselyn in her Toronto lab discovered how to visualize the neurons which are active during fear memory formation. They also developed a way to target and delete them, consequently deleting the memory. 

In Han et al. (2009), some beautiful genetic trickery was used to promote a 'kill switch' only in the neurons which are active during the memory formation.  This kill switch is the diphtheria toxin receptor.  Normally cells do not have this receptor, but when they promote this receptor artificially on the cell surface, an injection of diphtheria toxin will kill that cell, but not neighboring (dtr-free) cells.  The real impressive genetics is in promoting the diphtheria toxin receptor only in neurons active during memory formation.  To do this, the Josselyn lab used a marker for cell activity in amygdala neurons during memory formation, CREB.  Specifically, they used a transgenic mouse that expressed the diphtheria toxin receptor only when CREB activates cre.

So now with the memory encoded and the kill switch in place, they pull the trigger and inject diphtheria toxin into the mice. This kills all the amygdala cells that were active during memory formation (about 250 amygdala cells or so, Han et al., 2009 figure 1B).  They then test the mice again for freezing behavior.

Han et al., 2009 Figure 3

The second set of columns (CREB-cre, DT) is the experiment I have described.  Before any drug is injected the mice freeze in response to the tone, but after the diphtheria toxin (DT) injection, the mice freeze much less in response to the tone. What is really essential to this study is the control experiments that they ran. 

They wanted to make sure that just killing any 250 neurons in the amygdala didn't causes memory loss.  So instead of using the CREB promoter to activate cre (and thus the diphtheria toxin receptor) they used a control promoter (cntrl-cre, DT above) to promote cre in about the same number of neurons, but not dependent on neural activity.  In this case, there is no statistical difference in how much the mouse freezes in response to the tone. (compare the first two columns to each other.) 

Similarly, they wanted to make sure that the diphtheria toxin (DT) itself didn't erase the memories. They injected CREB that did not promote cre, and thus did not cause any diphtheria receptors to be expressed (CREB, DT). In this case, there was again no difference between pre and post DT injection.  Finally, they wanted to make sure it wasn't the CREB-cre construct itself, so they added the CREB-cre like normal, but did not inject the diphtheria toxin, so the receptors were expressed on these cells, but were not activated. In this case again, not difference in the amount of freezing. 

Because none of these control groups showed a difference in freezing, Josselyn could be confident that she had really shown that the specific neurons that encoded the memory were necessary for recalling the memory. 

They are also clear that the amygdala is not seriously damaged in this study, as the mice can re-learn the task after the specific neurons have been deleted.

One particularly interesting aspect of this study, which the authors do not discuss, is the number of neurons necessary for encoding a memory.  They delete hundreds of neurons.  I wonder if deleting half of them or even a quarter would result in the same erasure of the memory. How many neurons does it take to encode a memory?

Recently this concept of targeting proteins to only the active cells has been extended to include channel rhodopsin, the protein which allows cells to be activated by light.  Liu et al., (2012) was able to reactivate the neurons that were specifically active during the learning of a fear response. Stimulating these neurons caused the mouse to freeze, suggesting that stimulating these neurons reactivates the memory. This paper is covered thoroughly by Mo Costandi at Neurophilosophy.


© TheCellularScale

Han JH, Kushner SA, Yiu AP, Hsiang HL, Buch T, Waisman A, Bontempi B, Neve RL, Frankland PW, & Josselyn SA (2009). Selective erasure of a fear memory. Science (New York, N.Y.), 323 (5920), 1492-6 PMID: 19286560