Archive for the ‘Supramarginal gyrus’ Category

Surgeon holding scalpel.
Image by bethd821 via Flickr

Whether you are a carpenter, plumber, mechanic, electrician, surgeon or chef, your livelihood depends on a set of sturdy, reliable, well-honed, precision tools.  Similarly, neuroscientists depend on their electrodes, brain scanners, microscopes and more recently their genome sequencers.  This is because they are not just trying to dissect the brain – the physical organ – but also the psychological one.  As the billions of neurons connected by trillions of synapses process electrical impulses – a kind of neural information – it is the great endeavor of cognitive-molecular-neuro-psychology (or whatever you wish to call the art) to figure out how all of those neurons and connections come into being and how they process information in ways that lead to your personality, self-image, hopes, dreams, memories and the other wonderful aspects of your mental life.  How and why does information flow through the brain in the way it does? and how and why does it do so in different ways for different people? Some, for instance, have informally related Sigmund Freud‘s models of mental structure to a kind of plumbing wherein psychic energy was routed (or misrouted) through different structural aspects of the mind (pipes as it were).  Perhaps such a model was fitting for the great industrial era in which he lived – but perhaps not in today’s highly information-based, inter-connected and network-oriented era.  If our understanding of mental life is a product of our tools, then perhaps we should be sure that our modern tools are up to the job.

One recent paper reminded me of how important it is to double check the accuracy and precision of one’s tools was the research article, “Quantifying the heritability of task-related brain activation and performance during the N-back working memory task: A twin fMRI study” [doi:10.1016/j.biopsycho.2008.03.006] by Blokland et al..  In this report, the team summarizes the results of measurments of the brain activity – not structure – but rather activity as measured by their chosen tool, the MRI scanner.  This research team, based in UCLA and known as one of the best in the field, asks whether the so-called BOLD response (an indirect measure of neural activity) shows greater concordance in identical (monozygotic) vs. fraternal (dizygotic) twins.  To generate brain activity, the research team asked the subjects to perform a task called an N-back  workng memory task, which entails having to remember something that happend “N” times ago (click here for further explanation of N-back task or play it on your iphone).  If you’ve done this, you’ll know that its hard – maddeningly so – and it requires a lot of concentration, which, the researchers were counting on to generate activity in the prefrontal cortex.

After looking at the brain activity patterns of some 29 MZ pairs and 31 DZ pairs, the team asked if the patterns of brain activity in the lateral frontal cortex were more similar in the MZ pairs vs. the DZ pairs.  If so, then it would suggest that the scanning technology (measurement of the BOLD response) is sufficiently reliable and precise enough to detect the fraction of individual differences in brain activty that arise from additive genetic variation.  If one actually had such super-precise tool, then one could begin to dissect and tease apart aspects of human cognition that are regulated by individual genetic variation – a very super-precise and amazing tool – that might allow us to understand mental life in biologically-based terms (and not Freud’s plumbingesque analogies).  If only such a tool existed! Somewhat amazingly, the scanning tools did seem to be able to detect differences between the BOLD response correlations of MZ pairs vs. DZ pairs.  The BOLD response correlations were greater for MZ vs. DZ in the middle frontal gyrus, angular gyrus, supramarginal gyrus when activity for the 2-back task was compared to the 0-back task.  The team were cautious to extend these findings too far, since the standard deviations are large and the estimates of heritability for the BOLD response are rather low (11-36%), but, overall, the team suggests that the ability to use the fMRI methods in conjunction with genetic markers shows future promise.

Meanwhile, the literature of so-called “imaging-genetic” findings begins to grow in the literature.  I hope the tools are reliable and trustworthy enough to justify conclusions and lessons about human genetic variation and its role in mental life.  Will certainly keep this cautionary report in mind as I report on the cognitive genetics literature in the future.

Reblog this post [with Zemanta]

Read Full Post »

PhotoImage via Wikipedia Like most parents, I enjoy watching my children develop and marvel at the many similarities they bear to myself and my wife. The reshuffling of physical and behavioral features is always a topic of discussion and is the definitive icebreaker during uncomfortable silences with the inlaws. In some cases, the children are blessed with the better traits, but in other cases, there’s no option but to cringe when, “Look – wow, he really has your nose – hmmm”, is muttered. Most interesting, is the unfolding of patterns of behavior that unfold slowly with age. Differences in temperament and personality can instill great pride in parents but also can be a grating source of friction. One of my F1’s has recently taken to sessions of shrill, spine rattling, screaming which I hope will pass soon.

Why ? Many parents ask. “Have WE been raising him/her to do this ? – surely that’s what the neighbors must think”. “Is it something in the family ? I heard Aunt Marie was a bit of a screamer as a child – hmmm.”

In one of several of their landmark studies on the genetic regulation of pediatric brain development, Jay Giedd and colleagues, now provide in their recent paper, “Variance Decomposition of MRI-Based Covariance Maps Using Genetically-Informative Samples and Structural Equation Modeling”, a core framework on the relative contribution of genes vs. environment for the developing cortex. The paper is part of an ongoing longitudinal study of pediatric brain development at the Child Psychiatry branch at NIMH. Some 600 children participated – including identical twins, fraternal twins, siblings and singleton children.

The team used an analytical approach known as MACAAC (Mapping Anatomical Correlations Across the Cerebral Cortex) to ask how much does the variation in a single part of the brain co-vary with other parts ? Then the team used structural equation modeling to explore how much this co-variation might differ across identical twins vs. fraternal vs. siblings vs. age-matched singleton children. In locations where there is an high genetic contribution to co-variation in cortical thickness, identical twins should co-vary more tightly than fraternal twins or siblings etc. In this way, the team were able to parse out the relative influence of genes vs. environment to the developing brain.

In general terms, the team reports that a single genetic factor accounts for the majority of variation in cortical thickness, which they note may be consistent with a major mechanism of development of cortical layers involving the migration of neurons along radial glia. Genetic co-variances across separate locations in the brain were highest in the frontal cortex, middle temporal gyrus and left supramarginal gyrus. Interestingly, when environmental covariations were observed, they were usually restricted to just one hemisphere, while genetic covariations were often observed bilaterally.

Figure 5 of this paper is really incredible, it shows which areas of the cortex are more influenced by genes vs. environment. If I can just find the areas involved in screaming, the next time one of my neighbors looks askance at my F1, I’ll be able to explain.

Reblog this post [with Zemanta]

Read Full Post »