Thursday, November 18, 2010

Myelination of the corpus callosum in male and female rats following complex environment housing during adulthood

Inspired by yesterday's post on this review article I read this paper on myelination of the corpus callosum in male and female rats following complex environment housing during adulthood.  The authors were looking to see if putting adult rats (4 months) in an enriched environment would increase myelination in the corpus callosum.  Previous studies have shown that rats in an enriched environment grow more synapses and also increase the size number of astrocytes in the brain.  Myelination has been seen in rats raised in enriched environments but hadn't been well studied in adult rats before this study.

Just to jump to the end, the authors did not see and increase in myelination.  But they did see an increase in volume of the splenium of the corpus callosum which was driven by an increase in unmyelinated axons and glial cell processes.  They conclude that its unlikely that oligodendrocytes are increasing in size (since the amount of myelin stays the same) and so deduce that there must be more astrocytes in the splenium.  They tested the genu of the corpus callosum (at the front) and didn't see any changes.

I think this is wonderfully interesting: if rats don't increase the amount of myelin but do increase the number of supporting cells, then maybe we shouldn't be hypothesizing an increase in myelin with experience in humans.  Obviously I understand that rats and humans are very different, but this may be a situation in which the power of glial cells is being overlooked.  Maybe increasing the amount of myelin isn't what's necessary, rather an increase in the support for the electrical signal transmission.  Quality rather than quantity.  Having said that, I don't know what the unmyelinated axons are doing.....any suggestions?

Stereological point counting technique. Length of the corpus callosum is shown on a mid-sagittal section through a corpus callosum stained with osmium tetraoxide (each tic mark on the scale at the top equal to 0.5 mm) and the boundaries for the regions sampled (genu on the right, splenium on the left) are indicated by black lines (A). Toluidine blue stained section through the corpus callosum (B). The arrows (white) denote myelinated axons and the * indicate the location of two glial cell bodies. The area occupied by other material (unmyelinated axons and glial processes) is the amorphous, interstitial space surrounding the myelinated axons. Scale bar = 10 μm.

Markham JA, Herting MM, Luszpak AE, Juraska JM, Greenough WT.
Brain Res. 2009 Sep 8;1288:9-17. Epub 2009 Jul 9. 
PMID: 19596280

Wednesday, November 17, 2010

Change in the brain's white matter

There aren't many review articles on the cellular mechanisms through which changes in the brain's white matter can affect cognition, but this is the latest from R Douglas Fields who also wrote a review in 2005 entitled "Myelination: an overlooked mechanism of synaptic plasticity".  His reviews continue to be a wonderful resource for me because they cover not only the human cognitive experiments that are closest to my line of work, but also the animal behavioral and the cellular studies which are essential to the interpretation of MRI findings in living humans.

This article not only provides a beautiful picture of a couple of oligodendrocytes myelinating axons (below) which will probably be a great future figure for me, but also outlines the proposed mechanisms through which oligodendrocytes could know which axons are being taxed and how neuronal impulse activity could affect myelination.


Myelin that coats and insulates neuronal axons may control the propagation of electrical impulses in a manner that affects information processing.

The best new resource that this review has lead me to is this paper on myelination of the corpus callosum in male and female rats following complex environment housing during adulthood.  I'm really excited to read that paper (tomorrow?) and unpack their finding that:
Although the area of the splenium (posterior 20% of the callosum, which contains axons from visual cortical neurons) increased by about 10% following two months of EC [enriched] housing, the area occupied by myelinated axons was not influenced by adult housing condition. Instead, it was the area occupied by glial cell processes and unmyelinated axons which significantly increased following EC housing.
This means that after training, while myelination may increase (as has been suggested in human neuroimaging papers) there is also evidence for a relative decrease in myelin as astrocytes and unmyelinated axons take up more space.

Stay tuned, and thank you Dr Fields for another great review :)

Fields RD.
Science. 2010 Nov 5;330(6005):768-9. No abstract available.
PMID: 21051624

Tuesday, November 16, 2010

Brain development after birth differs between Neanderthals and modern humans

Why, you ask, is Kirstie writing about the differences in brain development after birth between Neanderthals and modern humans?  Well, it follows on from this report on NPR which makes the case for slower (when compared to Neanderthals) development being beneficial to humans.  I though instead of just reading NPR and taking their word for it I'd actually read the paper itself.

And let me tell you, there are a bunch of words I didn't know!!  Now I know how everyone else feels when I use all the MRI and psychology jargon!

Did you know that "in phylogenetics, a trait is derived if it is present in an organism, but was absent in the last common ancestor of the group being considered. This may also refer to structures that are not present in an organism, but were present in its ancestors, i.e. traits that have undergone secondary loss. Here the lack of a structure is a derived trait." (stolen from Wikipedia).

That definition allowed me to understand the conclusion that "the modern human pattern of brain development is derived compared to Neanderthals."  Basically the authors found that human brain development goes through a globularization phase (becoming more globe-like aka spherical - another word I had to look up!) that is not seen in Neanderthal development.

Neanderthal and modern human brains grow differently.
(A) For the virtual reconstruction of the Neanderthal neonate Le Moustier 2, CT scans of individual fragments were assembled on the computer. Fragments that were mirror-imaged to the other side are plotted in a darker shade. The gray surface represents estimated missing data. At birth, Neanderthals and modern humans have very similar endocranial volumes and shapes (red: Le Moustier 2; blue: modern human). (B) A principal component analysis of endocranial shape changes from birth (age group 1) to adulthood (age group 6). The convex hulls for modern humans (blue) are based on dental age groups. The fossil convex hull (red) is based on the Neanderthal adults only. The average developmental trajectory is plotted as a solid line. Endocranial mean shapes visualize the shape change during the modern human globularization phase between age groups 1 and 2. All fossils were reconstructed multiple times; each distribution of reconstructions falls within the respective semitransparent disks

This figure is pretty cool because it shows how a neonatal human brain looks very similar to a neonatal Neanderthal brain (top part) and then shows how the developmental trajectories differ.  The method's a little hard to explain but the authors do a good job in their supplementary materials if you want to check it out!!  I also think that the figure below (from a different paper) is a littler clearer on what's going on with the globularization: in this paper they compare humans to chimpanzees and see that the chimpanzees look very different to humans and like Neanderthals, don't show the dramatic postnatal globularization phase.

Endocranial shape space. (a) PC 1 versus PC 2, (b) PC 1 versus PC 3. Humans are shown in blue and chimpanzees in green. Age groups are coded by numbers 1–6. Semi-transparent convex hulls indicate the variation of age groups. Mean shapes of each age group are connected with a solid line to the subsequent age group. Thin lines are shown between bootstrapped age group means to demonstrate the low uncertainty of the mean trajectory caused by the cross-sectional samples. One fetal chimpanzee specimen (“f”) indicates that prenatal shape change in chimpanzees does not correspond to perinatal human shape change (from age group 1 to age group 2). Shape change along the PCs is visualized as mean shapes plus/minus 2 standard deviations (±2 SDVs) from the sample mean.
So, to get back to why on earth I'd care about this, I'll quote part of the NPR interview with the prinicipal investigator on this project: "We take a long time to grow up and become adults, and this has a lot of implications in terms of social organization, time for education, maturation of the brain, even psychology somehow."

I've suggested a conclusion from my data on white matter development that the slower a brain takes to mature the more cognitively able the child.  Which is pretty crazy: you'd probably think that a brain which matures really quickly would get to being as smart as an adult faster.  But that isn't what my results are showing and the longitudinal data will help to explain it further: is it that all smart people have less coherent white matter (which goes against some adult studies) or is it just that these clever children are taking longer to reach maturity (from a brain point of view)?  Maybe they're "ripening on the vine" like those delicious tomatoes at the farmers market ;)

Gunz P, Neubauer S, Maureille B, Hublin JJ.
Curr Biol. 2010 Nov 9;20(21):R921-2
PMID: 21056830

Monday, November 15, 2010

The link between callosal thickness and intelligence in healthy children and adolescents

My friend Jeremy sent me this paper from Arthur Toga's lab at UCLA on the link between callosal thickness and intelligence in healthy children and adolescents after he heard one of my many talks about how to interpret negative relationships between white matter and intelligence.

In this study the authors selected a wonderfully well matched sample of children and adolescents: in the 4 age groups (6-8, 9-11, 12-14 and 15-17) there were 25 girls, 25 boys, 4 left handed boys and 1 left handed girl.  That's pretty freakin' incredible and really allowed them to investigate which age group or gender was driving the results from the whole group of 200 participants.

For ever subject they investigated how the thickness of the corpus callosum (at multiple points around the midsagittal cross section) could predict intelligence (as measured by the WASI).  The only result which passed correction for multiple comparison was a negative correlation in the splenium.  This means that children and adolescents with a smaller splenium tend to score more highly on IQ tests.

Correlations between callosal thickness and intelligence (overall sample).

When they unpack this finding by looking at the individual age groups and the interaction with gender the story becomes much more unclear.  In one age group male and female participants have completely opposite correlations!  In addition the location of significant (uncorrected) correlations changes across age groups and genders.


Sex- and age-specific correlations between callosal thickness and intelligence.

What certainly can be concluded from this paper is that the relationships between brain structure and intelligence are not static: they change thought out development.  The authors make a lovely argument that negative relationships in children are not necessarily at odds with positive correlations in adults.  Another great aspect of their argument is that they provide me with some great references to support it :)

Obviously, I'm always happy to see the sentiment: "only additional longitudinal studies addressing callosal microstructure will resolve the true nature of developmental changes."  Here's hoping I can help!!

Luders E, Thompson PM, Narr KL, Zamanyan A, Chou YY, Gutman B, Dinov ID, Toga AW.
Neuroimage. 2010 Oct 13. [Epub ahead of print] 
PMID: 20932920

Sunday, November 14, 2010

Longitudinal changes in grey and white matter during adolescence

This paper on the longitudinal changes in grey and white matter during adolescence is the "first study to examine within-subject longitudinal changes in diffusion data in healthy adolescents".  24 teenagers, between 13 and 18 years old (at time one), returned 2.5 years after their first scan and the study investigates changes in their grey and white matter volumes and the fractional anisotropy (FA) of two major white matter tracts.

The results corroborate previous cross-sectional studies which have found increases in white matter volume and FA and decreases in grey matter volume.
Regions of grey (in blue–light blue) and white (in red–yellow) matter where volume shows significant (corrected p < 0.05) decreases and increases, respectively, with age over time.
White matter tracts (in red–yellow) showing significant (corrected p < 0.05) age-related FA increases over time in our group of adolescents.
The main reason I have this paper saved on my desk though, is for the statistical method they use to analyze longitudinal data (because I'm going to have to use them very soon!)  The authors created a design matrix which had regressors for each subject individually, to remove any within subject variance and then a regressor of interest which was their ages.  They orthogonalized that regressor to the subject regressors which (I believe) means that they were looking at the effects of age after the individual subject variance is accounted for, which is, after all, their question of interest :)

I also really liked this figure (below), for two reasons: One, I find it really interesting how little FA changes when you look across the sample.  It's only when you look at the pairs of data that you see an effect of age.  That's great evidence for the power of longitudinal studies: a cross sectional study wouldn't have been as sensitive to these changes. Two, its a change in parallel diffusivity that is driving this change in FA.  Not in perpendicular diffusivity.  I'm now really interested in seeing whether there is a qualitative difference between younger and older subjects.  Maybe myelination is driving a change in perpendicular diffusivity for children and reorganization, decreased tortuosity (curvy-ness) or increased axonal diameter is driving a change in parallel diffusivity in adolescence.  Who knows?  Stay tuned ;)
Scatterplots, with longitudinal data points connected by a line, of mean values of FA, parallel and perpendicular diffusivity from white matter regions showing significant relationship with age over time in adolescents. Orange lines indicate the three left-handed subjects.
Oh, and PS: the paper outlines very clearly how to deliniate the corticospinal tract and the arcuate fasciculus.  That'll be really helpful when I come to draw those tracts because there are so many different ways to do it that it's nice to be able to directly compare with previously published work :)

Giorgio A, Watkins KE, Chadwick M, James S, Winmill L, Douaud G, De Stefano N, Matthews PM, Smith SM, Johansen-Berg H, James AC.
Neuroimage. 2010 Jan 1;49(1):94-103. Epub 2009 Aug 11.
PMID: 19679191

The Illustrated Guide to a PhD

An absolutely wonderful illustrated guide to a PhD by Matt Might, a professor of computer science at the University of Utah.  Please quote him far and wide :)  This picture is just a tiny part of the story.

Saturday, November 13, 2010

Motivation Level


Grad student motivation across the billion years of study!

http://www.phdcomics.com/comics/archive.php?comicid=125

Work Output


An oldie but a goodie.

Graduate student work output throughout the week.

http://www.phdcomics.com/comics/archive.php?comicid=124

Matplotlib Gallery

Make any type of graph you can imagine!

I'm right at the very beginnings of being able to understand python but on Friday Cindee showed us this fantastic resource which doesn't only demonstrate what types of fancy graphs you can make in Matplotlib but also shows you the source code so you can actually do it!  Crazy, eh?

I was impressed at least.

Procrascorrelation


The title says it all.

So.
Freakin'
True.
http://www.phdcomics.com/comics/archive.php?comicid=1388