Wednesday, February 27, 2013

GABA, how exciting!

I would like to thank my good friend Anonymous for asking me a great question on a previous post.

Anonymous asks:
"Are there any known transmitters in the NS that activate both inhibitory receptor subtypes AND excitatory receptor subtypes? Or does every known transmitter activate EITHER a bunch of excitatory subtypes OR a bunch of inhibitory subtypes?"
 (btw. This doesn't qualify as a LMAYQ post because it's a real true question that someone directly asked, not a search term)

While I don't know of any instances of glutamate (excitatory) activating GABA (inhibitory) receptors or of GABA activating glutamate receptors, there is an interesting little way that GABA can activate an inhibitory receptor, but actually help excite the cell. 

GABA receptor (source)

 Here's how that works: GABA(A) receptors are permeable to chloride ions, and as the picture above shows, chloride ions (Cl-) are negatively charged. When GABA binds to the receptor, the receptor opens and chloride ions rush in, bringing their negative charge with them. This hyperpolarizes the cell, meaning it brings it lower and lower in total charge (membrane potential), which brings it further and further away from the threshold where it will fire an action potential.

BUT.... if there is a lot of chloride inside the cell already (or if the cell is resting more negatively than the chloride reversal potential), chloride will actually flow out of the cell, bringing its negative charge with it. Negative ions flowing out of the cell will depolarize the neuron increasing its total charge (membrane potential), which brings it closer and closer to the threshold where it will fire an action potential.

GABA reversing at -62mV (source)

A paper published last year in the Journal of Neuroscience shows that in a model of a hippocampal neuron, when a strong excitatory (glutamate) stimulation happens right after a GABA stimulation close by on the dendrite, the cell is actually more likely to fire than when the glutamate stimulation occurs on its own. This effect is dependent on the location of the GABA stimulation along the dendrite.

Chiang et al., 2012 Figure 4E (GPSP in the dendrite)

This figure shows that a GABA stimuation (first dotted line, blue trace) can push the glutamate (excitatory) stimulation (second dotted line, red trace) up to the point of firing an action potential (green trace). This paper also showed that GABA can still inhibit the action potential in these cells, it just has to be at the soma and almost the same time as the glutamatergic input.

Chiang et al., 2012 Figure 4G (GPSP in the soma)

 So there you have it, GABA enhancing the likelihood of an action potential and acting excitatory sometimes, and acting inhibitory other times. 

 © TheCellularScale Chiang PH, Wu PY, Kuo TW, Liu YC, Chan CF, Chien TC, Cheng JK, Huang YY, Chiu CD, & Lien CC (2012). GABA is depolarizing in hippocampal dentate granule cells of the adolescent and adult rats. The Journal of neuroscience : the official journal of the Society for Neuroscience, 32 (1), 62-7 PMID: 22219270

Sunday, February 24, 2013

Scientizing Art

I've always been fascinated with the way the eye moves around a piece of art.

Andrew Wyeth's "Christina's World" (or as I looked up "that painting of a girl in a field looking at a house")

This piece by Andrew Wyeth is an obvious example of an artist completely controlling your gaze. There are pretty much no options here. You look at the girl and then you follow her gaze to the house. You probably then take a quick glance at that other house/barn to the left, and then maybe follow the edge of the light circle around the houses. (It's my opinion that that is how the eye should go on this painting, but I have no eye tracking data to support it.)

A paper last year in PLoS One really tries to "scientize' this process by testing what factors determine the eye movements, and the 'clusters' where the eye tended to fall. Massaro et al., (2012) compare dynamic and static images and images that contain human subjects or nature subjects. Their cluster analysis overlaying classic paintings makes for quite interesting images:

The next installment at MoMA

This one is a dynamic human image. Each patch of color shows where the parts of the painting where the eye lingers (face, hands, ....crotch...). The authors do all sorts of interesting analysis on this and other paintings, having participants rate the painting for 'movement' or for 'aesthetic value' and since the paper is open access, it is free to people who may not have university access to journal publications. Anyone can read the whole thing here.

One interesting thing that the authors find is that pictures containing humans have fewer clusters than pictures of nature. I expect this is because certain aspects of humans (faces, hands ...crotches...) are so salient and the brain focuses directly on them, while all the branches of a tree for example have about equal 'meaning' for a person.

science creates modern art
 Another great image from this paper. The authors show how much gazing was done at different parts of a painting through a heat map. This one is a human static image. The end result is actually quite haunting because the place that you want to look is blanked out (sort of like a Magritte painting).

So here are my questions: If someone looks at a blank page, where does their eye naturally go? Is there some sort of common pattern that most people use just to scan an area? Do chimpanzees use a similar pattern to scan a blank page? Does everyone have their own unique scanning pattern? Or is it just pretty much random? 

And here's an idea for artists: Buy yourself an eye tracker and have customers come use it and stare at a blank page. Trace their eye movements and then create a dynamic painting (or T-shirt, or napkin drawing) that follows the person's natural scanning patterns. This would be the ultimate in commissioned custom art! (Then give me one for free, because I think this sounds like fun.)

© TheCellularScale
Massaro D, Savazzi F, Di Dio C, Freedberg D, Gallese V, Gilli G, & Marchetti A (2012). When art moves the eyes: a behavioral and eye-tracking study. PloS one, 7 (5) PMID: 22624007

Thursday, February 21, 2013

Birthing new neurons at night

By now it's well established that adults can grow new neurons.

Growing Neurons (source)
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.

Tamai et al.,, 2008 Figs 1B and 2D
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.

© TheCellularScale
Tamai S, Sanada K, & Fukada Y (2008). Time-of-day-dependent enhancement of adult neurogenesis in the hippocampus. PloS one, 3 (12) PMID: 19048107

Monday, February 18, 2013

How to Build a Neuron: The ultimate shortcut

We've gone through all the main steps for Building a Neuron, and  compiled them here. But there is one last shortcut that I absolutely have to tell you about. It's pretty much the ULTIMATE shortcut.

Full of Computational Models (source)
If you really want a computational model of a neuron, but just don't want to do the work to build one, even using the shortcuts I've already provided... you can use someone else's.

Model DB
 is a repository where scientists can upload their computational models for all to see and use. A README file is attached to each model and explains the basics of  the model. In addition, there is always a citation to the paper in which the model was first published, so you can read about how it was used. With these tools (and possible emails to the authors) you should be able to download and run a complete model and replicate the figures that someone uses in a paper. The model I mention is step 5 is there, and is an example of a complete and usable neuron with synaptic and intrinsic channels.

Model DB 

Model DB is helping advance the field of computational neuroscience in two ways.

First it allows for post-publication review, where people can make sure that the model does what the authors say it does. Having access to the actual code used to run the simulations is better than just reading the 'methods section' of a paper. As with all methods sections, you just can't explain everything well enough for it to be replicated
 exactly as performed.

Second, Model DB reduces the amount of overlapping work that scientists have to do. You've seen how tedious it can be to
 extract the Boltzmann curves of each intrinsic channel. Model DB allows you to see if someone has already done it for your cell type. You can use it just as it is, or you can follow the citations and re-extract it. In either case you have saved yourself valuable time.

One of the advantages of computational models is that they can be used to answer TONS of questions. Most of the time a huge amount of work is put into building the model, and then the model is used to answer a few questions, but the possibilities are endless. Having the models freely accessible allows for faster advancement in both computational neuroscience and the field of neuroscience in general. 

"ModelDB provides a resource for the computational neuroscience community that enables investigators to increase their understanding of published models by enabling them o run the models as published and build on them for further research. Its use can aid the field of computational neuroscience to enter a new era of expedited numerical experimentation." Migliore et al., 2003
Migliore M, Morse TM, Davison AP, Marenco L, Shepherd GM, & Hines ML (2003). ModelDB: making models publicly accessible to support computational neuroscience. Neuroinformatics, 1 (1), 135-9 PMID: 15055399

Hines ML, Morse T, Migliore M, Carnevale NT, & Shepherd GM (2004). ModelDB: A Database to Support Computational Neuroscience. Journal of computational neuroscience, 17 (1), 7-11 PMID: 15218350

Thursday, February 14, 2013

It's not you, it's my birth control

So, Valentine's Day, what better time to question the foundations of your relationship?

It's my brain that loves you (source)
Well, part of your relationship may be based on your Major Histocompatibility Complex (MHC) compatibility. The MHC is a cluster of genes that define which antigens get expressed on white blood cells. It is thought to control the ability of the body to recognize pathogens as 'other.' It is also thought that the more varied the genes in your MHC are, the more resistant to pathogens or parasites you are.

So what does the MHC have to do with your love life?
Well the most popular theory goes as such: If you want to have a healthy baby, you want to give it a varied MHC, therefore you want to find a man who has an MHC that is very different from your own.

And... Maybe you can detect whether a man has a MHC that is the same or different from yours through smell (maybe vision too). In 2005, a paper came out explaining that the Major Histocompatibility Complex (MHC) can be detected through smell, and (importantly) that women prefer the smell of men who have an MHC that is different from their own. (However another paper in 2008, did not replicate this preference)

Possible new fragrance? 

Now here's the real kicker: Taking oral contraceptives (birth control pills) might mess this preference up. Roberts et al., 2008 show that in an armpit sweat test (like this one), women on birth control showed more of a preference for the MHC similar men than the women not on birth control. If true, this could have implications for women starting relationships when they are either on or not on birth control. To take this to the greatest sensationalist extreme, you might pick the WRONG GUY because you were on birth control. However, just like I don't believe in destined, fated true love, I don't believe you need to have opposite MHCs to have a good relationship or healthy children.

Roberts et al. 2008 Figure 2C: Odor desirability ratings.
And not only that, I have somewhat of a problem with this graph and their data. As far as I can tell (I found the description to be pretty confusing), the white bars represent 'session 1' in which NO ONE was on the pill and then the gray bars represent 'session 2' when the women labeled 'pill' were actually on the pill, but the women labeled 'non-pill'  were still not on the pill. (following this?)  AND, 0 means that they liked the similar MHC and the dissimilar MHC guys equally, negative means the like the similar guys more and positive means they like the dissimilar guys more... (I told you this was confusing).

So my question is, why are the non-pill and pill users so different to begin with? Unless I am completely misunderstanding this graph, I would think the white bars should be similar, as they represent 'women who are not on birth control.' The huge difference between groups before the 'experimental treatment' should be a red flag: Something is already different between these women.

However, the pill session 1 (white) and pill session 2 (gray) bars are indeed different, and that is their 'main result.' Basically, women on the pill had an overall slight odor preference for MHC similar men, and the same women not on the pill had an odor preference for MHC dissimilar men.

So should you worry this Valentine's Day? Should you break up with your boyfriend because you were on birth control when you met? Should you spend a lot of time smelling your boyfriend's worn shirts analyzing how 'desirable' a scent the give off?

Probably not (unless you really like smelling sweaty shirts). There is more to relationship compatibility than histocompatibility, and making life-changing decisions based on possible olfactory disruptions due to birth control is just not a good idea.

Though if you are worried, you can read more about it at:

Context and Variation "will the pill mess up my ability to detect my one true love?"


First Nerve "pill goggles"

© TheCellularScale
Roberts SC, Gosling LM, Carter V, & Petrie M (2008). MHC-correlated odour preferences in humans and the use of oral contraceptives. Proceedings. Biological sciences / The Royal Society, 275 (1652), 2715-22 PMID: 18700206

Sunday, February 10, 2013

Why scientists should play games

I have just finished reading Jane McGonigal's book Reality is Broken: Why games make us better and how they can change the world. It is a fascinating book which presents a strong case for games (including video games) doing good in the world.

Reality is Broken by Jane McGonigal

I have to admit, part of me wanted to read this book to make me feel better about my own video game habit. It certainly helped solidify the vague ideas I had about what good they might be doing me.

Specifically, the book made me think that scientists of all people might benefit greatly from playing games. There is one major reason why:

Games make you more resistant to failure

If there is one thing that scientists need to persist in their research its resilience in the face of failure. If you didn't know this already, just start following some 'life in academia' bloggers on twitter. Failure is a staple of scientific life.

Just yesterday I awoke to a small grant rejection. I started thinking about just how many things I had applied for during my (still new) scientific career, and just what proportion of those applications had resulted in rejections. I tallied it up on a chart (similar to a failure C.V.), and discovered that for about every 3.5 things I have applied for, only one was successful. This includes grant applications, travel fellowships, paper submissions and re-submissions, and miscellaneous things like applying to be an SfN Neuroblogger. (I did not include abstract submissions or applications to graduate school.) I actually think this is a relatively good ratio, and I expect this ratio to get worse in the future, because the competition for the things I am applying for will be even tougher.

Part of the reason I wanted to calculate my success/attempt ratio was to see how many things I had actually applied for. I was glad that the list was long, and that I applied for lots of things, even if it means that my 'ratio' is the worse for it. I would posit that having a good success/attempt ratio is not really that great if you only ever apply for a few things that are easy to get.

In science, you will fail; there is absolutely no scientist EVER who hasn't been rejected from something.

So back to games. Reality is Broken explains that games teach you to persist in the face of failure, and that games increase your optimism.

"Learning to stay urgently optimistic in the face of failure is an important emotional strength that we can learn in games and apply to our real lives. When we're energized by failure, we develop emotional stamina. And emotional stamina makes it possible for us to hang on longer, to do much harder work, and to tackle more complex challenges. We need this kind of optimism in order to thrive as human beings." -Reality is Broken, chapter 4

When I think of my own resistance to failure (which is decent, but could be better), I think of my time spent learning from games that failure is not the end of the world. Ever since I repeatedly failed to jump Mario over the first Goomba, video games were teaching me to try again, and again, and again.

Mario and Goomba level 1. (source)
Jane McGonigal brings up Tetris, one of the most popular video games of all time. Tetris is a game with no possible outcome except failure. You keep playing until you lose, and yet the game is immensely fun and ultimately rewarding. Each time you fail you want to try again, and you feel that you will probably do better next time.

In summary, games reward persistence and desensitize you to failure. When you play video games you learn implicitly that trying again is worth it and that failing isn't the end of the world. These skills are great to have in life and are essential to have in an academic career.

Reality is Broken lists 13 other ways that games 'fix' reality. Some of these fixes are about personal betterment (like persistence in the face of failure), but some of these fixes are about how games can ultimately change the larger reality. Games that combat global warming, for example, or games like Fold-It that actually further scientific progress and human knowledge. Whether you already play games or not, you can get something out of this book.

A nice addition to this book is the appendix "Practical advice for gamers" in which Jane McGonigal lays out some guidelines for getting the most out of games. For example, one rule is to never play more that 21 hours in a week. While video games have benefits, there are problems that can result from compulsive video game play, and you shouldn't think think that you are doing something healthy if you play video games for 50 hours a week and completely ignore reality. The idea is that playing games can help you function in reality. If you never venture into reality, you won't make any use of the benefits that the game might have given you.

© TheCellularScale

Here are further reviews of Reality is Broken:
Ferguson, C. (2011). Reality is broken, and the video game research field along with it. PsycCRITIQUES, 56 (48) DOI: 10.1037/a0026131
Farhangi, S. (2012). Reality is broken to be rebuilt: how a gamer’s mindset can show science educators new ways of contribution to science and world? Cultural Studies of Science Education, 7 (4), 1037-1044 DOI: 10.1007/s11422-012-9426-y

Wednesday, February 6, 2013

JoVE: god of thunder, journal of techniques

If you don't know about the Journal of Visualized Experiments, now is the time to learn.

god of thunder, journal of techniques (source)
Methods sections of papers should contain enough detail that a scientist reading it could replicate the results of the paper. But this is rarely the case. Research in computational neuroscience has an advantage because the actual code used to run the simulations can be deposited and downloaded. But for experimental work, the nuances of exactly how to do each step in a process can get lost.

Protocol papers are often able to fully describe a process, but nothing can beat actually seeing the researchers performing the technique. For this there is JoVE.

You can get lost on their website watching fascinating 10 minute video after fascinating 10 minute video. For example, the very first video listed under 'neuroscience' when I checked it is called "Optogenetic activation of zebrafish somatosensory neurons using ChEF-tdTomato" and it shows you how stimulate the zebrafish neurons with light. But it doesn't just show you someone doing it, it shows each step in detail. How to modify the optic cable, how to position the zebrafish embryo, and even to be careful when using lasers. (Also, it taught me what the Pasteur Pipette can be used for.)

I think this is a great addition to scientific literature, and will be useful to many people. However, I still have some doubts about how easy it would be to replicate these techniques from the video alone. But fortunately accompanying the videos are detailed protocols with more details and equipment specs. 

I'd be interested to know if anyone has used a JoVE article and their sole resource and been able to replicate a technique successfully.
Palanca, A., & Sagasti, A. (2013). Optogenetic Activation of Zebrafish Somatosensory Neurons using ChEF-tdTomato Journal of Visualized Experiments (71) DOI: 10.3791/50184

Saturday, February 2, 2013

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

ResearchBlogging.orgSmith 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