Neurospeculation

A general guide to progression in the research PhD career path

noreply@blogger.com (Ryan Morehead) — Mon, 21 Mar 2011 11:04:00 +0000

I’m writing this in the hope that it can serve as a quick walkthrough on what to expect if you, or someone you know, is heading down the path of getting a doctorate in a research-heavy field.

Accompanying this progression through the ranks will almost inevitably be moves across the country or the world, which is no small thing. Also, remember that research PhDs (but rarely master's students) usually have their schooling paid for and are given a stipend throughout school.

The first step, after getting a bachelor’s degree, is graduate school. There are two general options for this, master’s and doctoral level.

Master’s: A lot of people in the sciences view a master’s degree as a stepping stone on the way to a PhD, but it is becoming more common for people to stop their education here and start making money, usually as an academic lab technician or in industry.

Doctoral: This is usually a PhD, but it might be other letters like DSci. Research PhDs can take anywhere from 3-7 or more years to complete, although every graduate school will tell you that their students average 5.5 years to completion, which is more or less the national average. There are, generally speaking, two phases of doctoral education: student and candidate.

A doctoral student is someone in the first two or three years of graduate study. At a certain point all students will take qualifying exams, which are also known as “quals,” “comps” or “prelims,” short for qualifying, comprehensive, and preliminary exams, respectively. These exams are usually very long and rigorous, with both a written and oral component which is tailored to individual student by a committee that also administers the exam. I read somewhere that the purpose of the exam is to make sure that the student’s knowledge fails at a sufficient level. In some programs, a master’s degree is awarded around the time of qualifying exams.

After all this, the student is now a candidate, which means that the student is now working on his or her dissertation research. This is usually very similar to the research that was being performed by the student for the previous two or three years but it also may have a bit of independence or break off in a new direction. At the end of graduate school, the student will have to have a signed dissertation, and it is also common to defend the dissertation to the dissertation committee in a format very similar to the oral part of quals.

Here’s where most people think of the “career” part starting. In reality, most students have been working contacts and lining up positions for a year or more before being awarded their PhD. Some people are even in faculty positions before they are awarded their doctoral degree, although that is becoming more and more rare.

For research PhDs, there are largely three options at this point: Postdoctoral research fellowship, industry, or faculty position. Postdocs are far and away the most common next-step, especially in biomedicine and life sciences, but there are also sometimes opportunities to start a faculty position right away, which is more common in psychology. Industry is another option, which usually pays a lot more. I don’t know much about industry careers, so I won’t discuss them any further.

Postdocs: These are usually 1-4 years per appointment and most people do 1-3 appointments before they land a faculty position. This is a very important part of a scientist’s career, as she is establishing herself as independent from her PhD advisor, and gaining new technical skills. Most people expect a new faculty member’s lab to continue the research from her last postdoc lab, rather than the lab where she did her PhD work.

Faculty: There are several different rungs of faculty spots. The general division is between tenure track and non-tenure track. You can usually tell the difference by the faculty member’s title. Non-tenured faculty are typically lecturers, adjunct or research professors. The tenure track progression is usually denoted by assistant professor (tenure track, but not tenured), then associate professor (tenured, half-way), and full professor which might also just be professor.

That’s it! There are a million caveats and things to add to this, but hopefully it’ll do as rough scaffolding.

A new test for hemispatial neglect

noreply@blogger.com (Ryan Morehead) — Tue, 11 Aug 2009 08:31:00 +0000

There’s an interesting article about a new neurological exam which found its genesis in an Eastchester High School classroom.

An AP Psychology teacher there was explaining hemispatial neglect, a disorder caused by brain damage in which the person is not consciously aware of either the left or right side of space or objects--including the patient’s own body.

During the discussion, one of the students asked the question, “What happens if you ask patients with neglect to clap their hands?” The teacher, Mr. Weisman, didn’t know. So he tracked down Dr. Rafael Llinás, a researcher at Johns Hopkins University, which in turn led to the development of what has been named the Eastchester Clapping Sign (ECS).

Here is a picture of one patient, who showed an improvement between the first and second day of administering ECS. You can see that he's clapping with one hand at the midline, near where his other hand should meet it.

The article in Annals of Neurology outlines how to perform and score the test:

ECS testing was performed as follows: (1) make sure patient's arms and hands are both down at their sides; and (2) ask patient to clap his or her hands. Grading was established as follows: ECS-2 = one-handed clap, respects midline; ECS-1 = searches in the contralateral hemispace for the other hand; ECS-0 = reaches over to clap against the plegic hand; and UTA = unable to assess, that is, does not follow the command; you can try pantomime.

The authors point out that this simple test can be done in 30 seconds, helping doctors to quickly administer the correct medicines to aid in stroke recovery.

This just goes to show that sometimes the best ideas come from people who aren’t involved in research. Mr. Weisman should be commended for following up on his students’ question.

References: dx.doi.org/10.1002/ana.21666

Precise Figures in Science

noreply@blogger.com (Ryan Morehead) — Thu, 05 Mar 2009 20:03:00 +0000

I was scanning the most recent issue of Brain Research Reviews when I came across an interesting figure.
Just take a moment and look at it:

If you're thinking "What in the world is that?" or "What is a Matisse painting doing in a neuroscience journal?" or perhaps some more colorful but equivalent phrase, congratulations. Me too.

The text accompanying the figure reads, "Receptor chunking. Isolated receptors statically scattered on the extracellular membrane (upper panel, adapted from H. Matisse, La Musique, 1910, oil on canvas), then cluster together into a “receptor chunk” after activation by the specific ligand ATP, and convey the feeling of emotional liberation into a function (lower panel, adapted from H. Matisse, La Dance, 1910, oil on canvas)." (emphasis mine)

What?

I later noticed an editorial in the same issue:
Free colour illustrations in the online version of articles
We are delighted to be able to inform you about an important development that is of benefit to the authors and readers of Brain Research.
Scientists in many disciplines need to be able to publish their work in colour, but the cost of printing figures in colour can be prohibitive and we realise that not all authors have sufficient funds to cover the charges.
Brain Research now offers the facility for authors to publish their illustrations in colour in the online version of the journal (in ScienceDirect: www.sciencedirect.com) at no cost - regardless of whether the illustrations appear in colour or black-and-white in the print journal.

I guess the authors got excited about this news and went a little overboard.
Figure and quotes taken from Volonté et al. Brain Research Reviews (59) November 2008, p1-8 dx.doi.org/10.1016/j.brainresrev.2008.04.004

Leave the Brain Out of It

noreply@blogger.com (Ryan Morehead) — Thu, 13 Nov 2008 18:31:00 +0000

The November 13^th issue of Nature has an opinion piece detailing some behavioral economics experiments, entitled ‘The Innovative Brain.’ It’s part of a essay series on innovation that I’ve found enjoyable so far.

The problem is, the research it talks about has nothing to do with the brain, other than all the subjects having one. This theme has been harped on in several other blogs I read, but it’s just annoying to me when such a big name journal puts out articles that throw in brain words to make things seem more interesting.

Although they claim to present ‘neurocognitive’ data, the piece is actually describes is a tendency in for entrepreneurs to be more prone to take a risk than managers in the Cambridge Gamble Task. Both groups, with mean ages slightly higher than 50 years old, differ in gambling behavior from their age matched controls. Managers gamble less money while entrepreneurs offer up more money. In a task that doesn’t assess risk taking, they are similar to their age group.

Adapted from B Sahakian et al.

I doubt many people will find this to be a shocking result. The article goes on to speculate that it may be possible to train young adults to be more innovative, or at least risk-tolerant, in entrepreneurship classes. Ok, maybe you can.

So what does this article have to do with the brain?

There are only a few parts of the article that mention it:

cold processes … are dependent upon the dorsolateral prefrontal cortex

then

hot processes are dependent on the medial and orbital sectors of the prefrontal cortex

and

These cognitive processes are intimately linked to brain neurochemistry, particularly to the neurotransmitter dopamine. Using single-dose psychostimulants to manipulate dopamine levels, we have seen modulation of risky decision-making on this task

There are a lot of things I could say about this. First of all, there is not a double dissociation between the areas of the prefrontal cortex that the authors mentioned and these tasks. I feel that a neuroscientist making such a claim is either being dishonest or, well, not really a neuroscientist.

Second, the ‘single-dose psychostimulant’ experiment the authors cite involves children diagnosed with AD/HD, not cognitively normal 50 year old businessmen. The stimulant they used was methylphenidate, commonly known as Ritalin, which is well known to exert opposite effects when administered to AD/HD children versus normal adults. So they gave it to AD/HD kids, and the kids bet less; adults could be expected to bet more money on Ritalin.

That is all, however, beside the point. An essay about the ‘Innovative Brain’ would talk specifically about how brain structures or nuclei are thought to contribute to innovation. It would discuss neuroscientific techniques like EEG, MRI, PET, or MEG in humans and perhaps more invasive procedures in animals. It would be much closer to this New Yorker article or even this Nature essay (requires subscription).

I’ll conclude with this: If you’re not really talking about neuroscience, leave the brain out of it, because you’re probably making gross generalizations and leaving out a lot of relevant information. The truth is, we don’t really know how any of these complex behaviors come about, it’s not honest to pretend we do, especially when talking to a lay audience.

References

B Sahakian et al. doi:10.1038/456168a

EE Devito et al. doi:10.1016/j.biopsych.2008.04.017

20th Anniversary Edition of Neuron

noreply@blogger.com (Ryan Morehead) — Mon, 10 Nov 2008 19:52:00 +0000

Neuron, a well respected journal, recently put out its 20th Anniversary Edition.

The good news is that the online edition is free to the public.

Normally a free edition of a neuroscience journal wouldn't mean much, but this issue has a lot of perspective pieces written by experts on the past, present, and future of their fields. These articles seem to be written for an intelligent lay audience, which is fantastic. It's always exciting to come across things like this, that explain the recent history of a scientific subfield in a way that is only normally done in a classroom or private discussion with a professor.

Take a look, there's some good stuff.

Stereotaxic Surgery

noreply@blogger.com (Ryan Morehead) — Wed, 15 Oct 2008 18:31:00 +0000

Last night I ran into an article on JoVE.com, the Journal of Visualized Experiments, which is a great example of the technique I'm using for my undergraduate thesis. There are some differences, but by and large it's a great window into my lab days.

Normally our mice are euthanized directly following surgery, but recently one of the grad students I work with had to do some lesions to induce sub-threshold Parkinson's disease. This made it necessary to take the precautions against infection and include some of the post-op recovery steps that are shown in the video.

That stage of her project was actually easier than what you'll see on JoVE. The crew at Tufts is implanting small screws to the skull to secure a permanent microdialysis probe, while all we needed to do was temporarily insert a cannula to inject a microliter of 6-Hydroxydopamine solution.

Anyway, check out the video, and the rest of JoVE for that matter.

One caveat, this video is not for the squeamish. It shows surgery on live animals.

Survivable Stereotaxic Surgery in Rodents

From Spikes to Decisions: Part 2

noreply@blogger.com (Ryan Morehead) — Sun, 14 Sep 2008 22:46:00 +0000

Spatial Awareness

Space is an interesting concept, one we often don’t think about. It’s something that has to be calculated to do something as simple as walk across the room, or as complicated as walking across a city. It’s an abstract thing, and by that I mean that we have no sensory receptors for space; it’s something that has to be generated as an idea in our heads. Psychologists call what’s generated an internal map.

In 1971, the neuroscientists John O’Keefe and Jonathan Dostrovsky found nerve cells that fire differently according to where an animal is in an enclosure. This was particularly significant because the rat’s position in the maze could be measured, which allowed the researchers to correlate specific cell firing with specific locations. They dubbed these neurons, found throughout the hippocampus, place cells.

Resorting to a graphical representation is probably the best way to illustrate place cell function. I’ve borrowed a handy flash animation from University of Bristol’s spatial memory page to help with that (doesn't work in an RSS reader):

As the animal walks around the enclosure and checks out its environment, certain cells will fire at certain times, and by charting this firing relative to the animal’s position, the researcher can work out the place field of the neuron. Once a rat has learned a space, it can return weeks later and place cells will fire in a very similar way to the first time it walked around the space. Yet if the researcher moves the distal (far away) sensory cues—by rotating colored shapes that mark certain walls while the rat is out of the enclosure or distracted—the firing of these cells will change in proportion to the amount of rotation.

The above examples show that a rat makes the primary judgment of where it is via distal sensory cues and that place cell firing is directly related to this decision. Itzhak Fried, a UCLA neurosurgeon, and his collaborators have demonstrated the same principles in human epileptic patients.

We’re visual creatures, and for most of us it may be hard to separate ideas of space from our visual world, but internal maps and place cell firing aren’t wholly dependent on sight. Bats, whales, and blind people all navigate through space without visual cues. It may come as no surprise then, that researchers have shown that distal visual cues aren’t the only thing controlling the firing of place cells in rats. The input is polysensory, integrating all of the five senses, motor output to the limbs, the vestibular system (loopy things in the ear) and, of course, memory.

An illustration of this polysensory input is an experiment where the walls were quickly dropped as a rat ran down a long hallway. The walls and the symbols that researchers placed on them were all the rat could see before, and it would have a completely different environment after dropping the walls. If distal cues were all that determined the rat’s place cell firing, then they would have seen a change, but the cells continued to fire as they did before the walls were dropped. In this instance, the rat wasn't fooled because the act of running continuously was enough to let the rat know it didn't go anywhere new, and the cells fired the same way as a result.

To sum up this section, when place cell firing is overlaid on both time and location of a rat’s movements, there is the ability to begin deciphering the neural code of internal maps, and then move both down and upstream of the hippocampus to start figuring out the inputs. By doing this, scientists have found the major determinant input of place cell firing, grid cells.

Reward Prediction

Dopamine was long thought to be the chemical responsible for pleasure, but it’s now thought of as responsible for “wanting” or motivational urges. It’s also involved in other things, like movement and suppression of the hormone prolactin, but I’ll only refer to dopamine in its reward related role.

By recording the action potentials (spikes or firing) of dopaminergic cells of the substantia nigra and ventral tegmental area, two inter-related areas in the midbrain, scientists have been able to find what’s known as the dopamine reward error prediction signal. All the figures I’ll use below come from Wolfrum Schultz’s scholarpedia page on reward signals.

The least ambiguous way I can think of to illustrate this principle is to have the reader imagine a monkey sitting in front of a screen, with a little tube at his mouth for administering drops of juice. On the screen, different pictures are being flashed and after certain ones he’ll receive a drop of juice. Researchers call the pictures that are paired with juice a conditioned stimulus (CS) because there’s nothing inherent in a random picture that tells the monkey a reward is coming; he has to learn the relationship.

In the figure below, you can see how these cells respond to a reward that the monkey didn’t know was coming:

In this figure and the ones that follow, the individual cells being recorded are shown in rows from top to bottom. The spikes of these cells are shown left to right as they occur over about 3 seconds. At the top they’re all summed, so it’s easier to see when a lot of them fire together.

Because the monkey doesn’t know that the picture means a reward is coming, the cells fire a lot in response to the surprise juice. This is pretty much the pattern they follow, until the monkey has learned which pictures come before a drop of juice. Once the monkey learns, the dopamine cells fire like this:

Two things are very clear here. The first is that the cells all fire at essentially the same moment in response to the conditioned stimulus. The second is that the reward elicits no change in the normal firing of the cells. From this figure, the idea that dopamine doesn’t correlate with the pleasure of a reward should make sense.

Dopaminergic firing will continue in this pattern if the experimental conditions stay the same, and a reward always follows a conditioned stimulus. The experiment can be modified, however, and a stimulus that used to signal a reward will no longer do so.

When this happens, the monkey’s dopaminergic cells show an interesting firing pattern:

The response to the CS is the same, but there’s a period where the neurons are completely shut down because there was no reward when it was expected.

All three of these responses are distinctly correlated with stimuli in the world, in the same way that place cells fire in specific locations.

These two wonders of the brain, place cells and the dopamine reward signal, represent the neurological correlates of mental percepts for which there are no sensory organs. Researchers have spent several decades refining knowledge of both so that we now know just how to find the cell activity and, for the most part, what it means.

Can we take these two signals and look at them simultaneously to discover anything useful?

This is the question that a recent paper by Adam Johnson and David Redish asks. It also looks at how you would frame and experiment to find out. I think it's a very exciting proposal, and I'll go over it in part 3 of this series, along with some of my own thoughts on the matter.

For more information on either of the topics I talked about above, I recommend checking out University of Bristol's spatial memory page, and Wolfrum Schultz's scholarpedia article on reward signals, which are both linked below.

References:

University of Bristol’s neuroscience website: http://www.bristol.ac.uk/synaptic/research/projects/memory/spatialmem.htm

The Mosers' annual review article on Place Cells, Grid Cells, and the Brain’s Spatial Representation System: dx.doi.org/10.1146/annurev.neuro.31.061307.090723

Schultz’s scholarpedia page:

http://www.scholarpedia.org/article/Reward_signals

Schultz’s annual review article on reward: dx.doi.org/10.1146/annurev.psych.56.091103.070229

From Spikes to Decisions: Part 1

noreply@blogger.com (Ryan Morehead) — Fri, 12 Sep 2008 20:40:00 +0000

In 1799, in the Nile Delta town of Rosetta, Napoleon’s army came across three passages inscribed in a slab of black basalt. Each segment was actually the same message written three times, each in a different language. Hieroglyphics were on the top, then demotic, and Greek at the bottom. The demotic was deciphered rather easily, but the hieroglyphics remained a mystery for several years. At the time, no one had a clue what the glyphs meant; the predominant view held that it was just picture writing, not a phonetic alphabet. This view was challenged by James Young, and then shown to be false by a man named Jean-François Champollion.

Champollion, who could read both Greek and Coptic, was able to figure out the seven ancient demotic signs that were still alive in the Coptic language. Looking at how these signs were used, he was able to work out their meaning. He then began tracing the demotic signs back to hieroglyphics. By working out what some hieroglyphs stood for, he could then make inroads into the rest of the passage.

With his deciphered passage in hand, Champollion traveled to Egypt and removed the shroud which had covered ancient Egyptian language and history for so long.

At first glance, a scribbled-on slab of black basalt has little in common with brain research. However, one of the major approaches to neural science—deciphering neural code from sensory input—is essentially the same process linguists used with the Rosetta Stone. Simply speaking, as long as there is a sensory input that changes neural firing, there is the potential to decipher that firing. For vision, this could be a white screen with a black vertical bar, for hearing, a “bah bah” as opposed to a “gah gah” sound, for touch, a tap on the finger, and so on. Although the technical side is quite complicated, it is at its core a process of translation.

Over the past hundred years, science has been able to discover a lot about the brain and how it functions. It’s no small wonder that some of the greatest advances in our understanding have been in the area of vision, where it’s relatively easy to control experiments in order for the subject to see only what the researcher is looking to study. If the picture being projected onto the retina is known, then adding, removing or changing the picture in a systematic way can illuminate how and where in the brain neurons change their firing patterns.

The problem is, many of the things we are most interested in—consciousness, problem-solving, emotion, episodic memory, even adding or subtracting—are intangible states or mechanisms of the mind. These are things that happen inside a creature’s head, and there are not necessarily any outward signs that anything is occurring.

For instance, even figuring out the mood of a person is a precarious undertaking. Take something like happiness. Someone can say they’re happy, but what are they feeling when they say they’re happy? How about an animal’s emotional state? There is no sure way to objectively know what any creature is thinking or feeling; it’s even impossible to know that other people are conscious. This makes it significantly challenging to find an inroad into the biological basis of some of the biggest questions about ourselves.

Brain research is complicated by this factor, but that doesn’t mean people haven’t been trying to figure it out anyway. A lot of psychology and neuroscience experiments are actually designed to discover neural and behavioral signs of a mental state, so we can make some significant progress in these areas. I would like to focus on one area in which I think we are about to put the biological basis of two separate mental phenomena.

These abstract mental functions are, I think, well defined in terms of neural firing. By well defined, I mean that neuroscientists have known about them for decades and done thousands of experiments to both directly and indirectly confirm the correlation between the biology and the psychological construct.

The first concept, spatial awareness, has found a correlate in place cells, which are located throughout the hippocampus. The second is the reward prediction signal, produced by the dopaminergic neurons of the midbrain.

In upcoming posts, I’ll summarize the functioning of these two systems, describe a paper that asks if they could be integrated, and discuss why I think it would be an exciting development.

References:

Rosetta Stone Sites:

BBC - http://www.bbc.co.uk/history/ancient/egyptians/decipherment_06.shtml

About.com - http://ancienthistory.about.com/cs/egypt/p/rosettastone.htm

One of my paragraphs is a summary/paraphrase of the bottom of this site - http://www.ancientegypt.co.uk/writing/rosetta.html

New Post Coming Soon...

noreply@blogger.com (Ryan Morehead) — Wed, 03 Sep 2008 21:15:00 +0000

I'll have a new post on "Integrating hippocampus and striatum in decision-making" pretty soon. It's a very cool topic if you ask me.

The school semester just started and I've been a lot busier than I anticipated.

I'll also fix the grammar/typo problems on the autism post because, well, they're embarrassing.

Autism at the Brain Level

noreply@blogger.com (Ryan Morehead) — Tue, 19 Aug 2008 18:59:00 +0000

Autism is a disorder characterized by impairments in social interaction, deficits in language use or development, and the appearance of repetitive or ritualized behaviors. It's important to note that the degree of disability of those affected by autism falls along a spectrum. On one end there's remarkably high functioning individuals like Daniel Tammet , on the other is an adult living in a world of frustration and misunderstanding because he can't communicate at all. This irregularity in behavior is mirrored in the pathology affecting the structures of the brain.

David Amaral et al. reviewed the current knowledge this disease in a paper published in the March edition of Trends in Neurosciences. Their review covers a field of study that is saturated with low sample sizes, divergent investigation techniques, and dissimilar cohorts.

Small sample sizes make it very hard to generalize to the autistic population as a whole. Disparate research methods, such as magnetic resonance imaging (MRI) and postmortem tissue analysis (counting the number of neurons, synapses, glia, etc.), do not at the same thing, and this makes it hard to form connections between the different studies. The papers surveyed for review were also frequently not conducted on subjects with the same clinical diagnoses. For instance, one MRI study was on high functioning individuals with no retardation or seizures while a postmortem was the exact opposite; this seemed to be the trend rather than the exception. None the less, it seems that the authors were able to make some sense of the chaos.

Total brain volume tests (measured by head circumference or MRI studies in young children) indicate a period of abnormal growth in the first year of life, in turn leading to an enlarged brain for the remainder of childhood. This, however, awaits validation by a more rigorous MRI study comparing brain volumes over several years.

It has been suggested that this abnormal growth may be larger in white matter—the area made up of long distance wiring of neurons and associated support cells. A few studies have shown this, but it is unclear if the disproportional size of white matter continues into adult brains. The grey matter's smaller increases in size, however, have been shown to persist in a few studies. Diffusion tensor imaging studies (a way of showing the length and direction axon bundles) hint at an increase in the white matter maturity of toddlers.

There have been several attempts at isolating these enlargements to certain regions; the most reliable area to see increases is the prefrontal cortex. However, this area of research seems particularly troubled by inconsistencies in experimental design, as the authors politely pointed out: "A perusal of this literature emphasizes the need for the field of developmental neuropathology to establish a systematic approach to evaluating abnormal brain development."

Postmortem studies on the cellular level have been limited in a similar way, with very small sample sizes and a lack of quantitative analysis. The best idea to come out of this line of investigation is a question posed by Casanova and his collaborators on the structure and organization of minicolumns in the cortex. A minicolumn is thought by many to be the individual functional unit of the brain. There is an excellent description of cortical columns in this article describing a team in Switzerland's attempts to model one. They are organized in the cortex in a manner similar to skyscrapers in a city, except this city would cover the world and be filled only with skyscrapers. Casanova suggested that these columns are abnormal in both quantity and width in the autistic brain. If minicolumns are indeed the functional units of the brain, abnormalities in their overall makeup would certainly cause problems.

There have also been abnormalities—distinct from those mentioned above—documented in specific brain areas. The two most easily identified regions are the cerebellum and the amygdala.

A very consistent finding of postmortem studies of the autistic cerebellum is a decreased density of Purkinje cells, especially in the outer cortex of the hemispheres. These cells make up the majority of the cerebellum, which necessary in coordinating complex movements. The authors note that this is at odds with some MRI research showing an enlarged cerebellum in autistics, but this is largely due to significant differences (high functioning vs. not, etc) between the patients studied.

During the period of abnormal growth discussed earlier, the amygdala also seems to increase in size and this may continue into late childhood. Increased amygdala size is correlated with many things, among them anxiety and impaired social skills. Further abnormalities exist when autistic boys hit puberty, where the amygdalar growth typically seen in teenage boys is nonexistent. Studies on older males have shown either no difference or smaller amygdalar volumes than controls.

After reading this review, it is obvious that the research into the biological basis of autism is in serious need of organization. The lack of continuity between methods and the differences in patients studied only adds to the difficulty in understanding the pathology of autism. The situation seems similar to that which has plagued research into other disorders like schizophrenia and anxiety/depression for years. Autism research could clearly benefit from some sort of a collaborative framework or organizing body.

Even with the shortfalls of the current state of research, there are a few areas of consonant findings that I can sum up here. During the first year of life, there is a period of abnormal enlargement in the brains of autistic boys. Both white and grey matter is increased, but white matter much more so. It is not clear that this enlargement continues through childhood. In this same time period, the amygdala is enlarged disproportionally but does not increase in size during puberty, as is normal. It is also likely that autistics will have a decreased number of Purkinje cells in the cerebellum.

These findings are no small achievement, and are helpful in developing animal models of the disorder for research. For instance, the lab I volunteer in recently did a study comparing the evoked dopamine release in the prefrontal cortex of mice that have decreased Purkinje cell counts (Lurcher mice chimeras) versus wild type mice. These Lurcher chimeras display repetitive stereotyped behaviors that are similar to those seen in autism.

The mouse model isn't perfect—and never will be—but research to further define the disease on a human level is absolutely necessary in guiding us at the basic stages.

References:

Amaral et al. Trends in Neurosciences. 31(3) 137-145

dx.doi.org/10.1016/j.tins.2007.12.005

Encephalon #52

noreply@blogger.com (Ryan Morehead) — Tue, 19 Aug 2008 03:58:00 +0000

The new brain blog carnival Encephalon #52 is up over at Ourobros.

The format this time around is Q&A, with a reader hypothetically asking a question that a blog author answers.

What's more is I actually made it onto the list!

I really recommend checking it out; I always enjoy reading through the articles.

Neurogenesis and Depression: What’s really going on?

noreply@blogger.com (Ryan Morehead) — Tue, 05 Aug 2008 16:47:00 +0000

Depression is a pervasive illness that is not well understood despite being the subject of much intense research. For a long time, a lack of serotonin was thought to be the lead culprit (sometimes combined with norepinephrine and/or dopamine). The old idea was pretty much that if doctors could pop a depressed patient's head open and pour in a glass of serotonin, the problem would be solved. This assumption, known as the monoamine-deficiency hypothesis, is viewed as an antiquated oversimplification today. The reason for this is simple.

Prozac, and other selective serotonin reuptake inhibitors (SSRIs), work by blocking the nerve cells from transporting serotonin back into the cell after it's been released. In a way, this is like stuffing a rag in the drain of a kitchen sink with the water running. If you block the transporter, the level of serotonin will rise, just like water in the sink, because it has nowhere to go. So, by administering an SSRI, a doctor can "block off the drain" and raise brain serotonin levels within several hours. The problem with this, as a lot of people are aware, is that it takes one or two months of SSRI treatment to see an antidepressant effect. This lag in the effect of SSRIs makes it pretty clear that depression is not an easy-to-fix "chemical imbalance."

So why is there such a gap in time between administration of SSRIs and response? To explain, a little background is needed.

In order to model depression in animal models, researchers use stress paradigms (paradigm in this sense just applies to the technique and its theoretical justification) to induce behavioral states that are considered analogs of human depression. Chronic stress, mostly through hormones called glucocorticoids, is known to significantly limit neurogenesis in the hippocampus of animals. Neurogenesis is a term that more or less encapsulates the birth, survival, growth, and movement of new nerve cells in adults. Researchers have shown that depression decreases neurogenesis by injecting a fluorescent marker known as BrdU into 'depressed' mice. BrdU is a chemical that attaches to cells that have recently split, or been 'born.' After subjecting mice to a stress paradigm, and observing depressed behavior, the brains can be checked for neurogenesis.

Normal neurogenesis looks something like this:

In depression, these cells do not make it through the survival phase.

Over the years, experimental evidence has shown that SSRIs do promote neurogenesis in a brain region called the hippocampus. Neurogenesis, while far from the only effect of SSRIs, was certainly present when mice improved in depressive symptoms. After observing this, many people wondered whether this were the elusive mechanism through which SSRIs have their antidepressant effect.

So was the neurogenesis a necessary mechanism or just a coincidence? In a 2003 study, researchers irradiated the hippocampus of mice that received antidepressants (this is similar to cancer treatments, lead shields are used to protect the adjacent areas) and succeeded in eliminating 87% of the new cells. With the loss of neurogenesis, the behavioral recovery that normally coincides with administering these drugs to depressed mice was absent.

This was reasonably conclusive evidence that neurogenesis was necessary for SSRIs to have their effect. In addition, the time course of antidepressant effect in clinical cases, four to eight weeks, is about the same time that it takes for new cells to be born and then integrate themselves into the neural network of the hippocampus in these rodent studies.

Seems straightforward right? When an animal is stressed, it releases glucocorticoids, which stop neurogenesis, and then the animal becomes depressed. Give it antidepressants, which kick start neurogenesis, and it goes back to normal. There would seem to be a negative correlation between neurogenesis and depression. In other words, neurogenesis goes up and depression goes down, or vice versa. Well, not so much.

A recently published a paper in the journal Biological Psychiatry shows evidence that neurogenesis is causal in relieving depression, but not in starting it.

The researchers again used irradiation to suppress neurogenesis, and a paradigm known as unpredictable chronic mild stress (UCMS) to induce a depressed state. UCMS basically freaks out the mouse by repeatedly subjecting it to things like cage tilting, damp sawdust (lining the bottom of the cage), predator sounds, putting the mouse into another male's empty cage, and shifting the light/dark cycles.

They quantified the effects of this stress through assessment of the animal's coat state, weight, a splash test, the novelty-suppressed feeding (NSF) test and an actimiter. The coat state is an obvious sign that UCMS is working; a stressed mouse won't groom itself as much and it may start to fluctuate in weight. The other tests look for behavior analogous to depression in humans.

The paper actually has a nice graphic to illustrate the experimental design:

The paper contains about four experimental conditions, and I'll address them in the sequence that the authors did.

In the first set of conditions, the authors were simply looking to see if, when subjected to UCMS, there was a difference between mice who had their hippocampus irradiated and those that didn't. In other words, were mice without hippocampal neurogenesis more vulnerable to stress and would they show depressive signs quicker than normal mice?

The answer was no:

In the above graph, and the ones that follow, a higher score indicates a worse coat condition. A low score can be interpreted as a "happier" mouse.

As you can see, there is virtually no difference in the behavioral effects of stress on the two groups of mice. The authors' interpretation of these results was that neurogenesis doesn't play a causal role in the pathogenesis of depression.

This is a significant finding because in the past it's been hard to dissociate neurogenesis and depression. Hippocampal neurogenesis is increased by nearly every antidepressant drug. Also, fluoxetine, imiprimine (a potent tricyclic antidepressant), and cannibinoid antidepressant therapies have been shown to require neurogenesis to have their effect.

So the question was, if neurogenesis isn't causing depressive symptoms, is it always needed to relieve them?

The authors decided to do a larger set of three experiments, where they would split the conditions appropriately. The only difference between the graphs below is the drug used in each. Unlike above, all of the mice discussed below were subject to the UCMS paradigm.

The first two graphs are basically a replication of the earlier finding that the monoaminergic drugs fluoxetine and imiprimine fail to relieve depression when neurogenesis is suppressed:

As expected, only the groups that received the monoaminergic antidepressants with no irradiation were unaffected by the UCMS.

The next two graphs show the same thing, but with different drugs. The experimental drugs shown are SSR149415, a V_1breceptor antagonist, and SSR125543, a CRF₁receptor antagonist (antagonists inhibit the function of a receptor). Both of these drugs work on the HPA axis, a neuroendocrine system that regulates a plethora of body functions. The HPA axis is usually overactive or somehow dysregulated in anxious or depressed humans, leading to an abnormally high level of glucocorticoids. This is not a good thing, seeing as glucocorticoids regulate neuronal survival, the size of structures like the hippocampus, the storage of new memories and the emotional appraisal of events. Too much of them, and you get things like hippocampal atrophy and a reduction in neuropil.

These two drugs inhibit processes in the HPA axis that are central to the release of glucocorticoids. To return to the kitchen sink simile, it's like turning down the faucet.

There are several novel drugs like SSR149415 and SSR125543 in clinical trials for anxiety and depression right now, and the authors wanted to see if they were also reliant on neurogenesis.

Here were the results:

Both groups responded to the treatment whether or not they were irradiated. So it seems that these drugs act on a different mechanism.

The authors suggest a model to explain their findings, whereby the hippocampal neurogenesis acts to repair the inhibition of the HPA axis.

T-shaped lines indicate a decrease, arrows an increase.

The general idea is that these new antidepressants potentially skip a step and directly influence the HPA axis.

This study is helpful in that it tells us something about the role of neurogenesis in depression. However, V_1band CRF₁receptor antagonists will not be game changers. It seems that they don't work any faster than current medications, and the irradiation factor is clinically irrelevant.

My personal opinion is that we won't make any real breakthroughs until we define the neural circuits involved in mood modulation and discover how the flow of information through them is affected by the disease.

All graphs and figures were adapted from Surget et al.

References:

Surget et al. Biol Psychiatry. 2008 Aug 15:64(4):293-301. Epub 2008 Apr 11. dx.doi.org/10.1016/j.biopsych.2008.02.022
Pariante CM and Lightman SL. Trends Neurosci. 2008 Jul 31. [Epub ahead of print] dx.doi.org/10.1016/j.tins.06006

Beginning

noreply@blogger.com (Ryan Morehead) — Wed, 30 Jul 2008 15:15:00 +0000

I'm starting this blog as a way to help synthesize papers that I read. I'm an undergraduate at the University of Memphis, and to be honest there just aren't that many people around that have the time or inclination to talk about neuroscience.

My goal is to summarize and speculate on at least one peer reviewed paper a week. Hopefully, my analysis will be accurate. If it's not, I welcome critiques of my thinking; all I really care about is learning more about brains.

I currently volunteer in Chuck Blaha's lab. Under the direction of his grad students, Deranda and Tiffany, I help to do research on Parkinson's disease, addiction disorders, and in general anything that has to do with dopamine. We use stereotaxic rigs to do in vivo amperometry on anesthetized mice (all I really do at this point is fabricate electrodes, break down the stereotaxic and help analyze data).

I should have my first real post up soon!