john hawks weblog

paleoanthropology, genetics and evolution

fMRI

  • Cultural neuroscience and pedigree-based neuroimaging

    Tue, 2013-04-23 09:34 -- John Hawks

    I've been meaning for awhile to link Daniel Lende's thoughtful post on how cultural neuroscience relates to anthropology: "Advances in cultural neuroscience". This is a field that has been taking shape over the last few years, with psychologists, geneticists and neuroscientists collaborating to take on questions about how culture and genetics interact to produce human behavior. But breaking down human behavior into measurable chunks is not so easy:

    As for theoretical models, cultural psychology has generally taken a trait-based approach to culture – individualism vs. collectivism, for example. This approach, and its increasing use of genetics, has led to a more factor-based approach to explaining variation. The culture measure contributes this much to the outcome variable, and the gene marker this much. This discrete approach to measuring variables is both powerful and reductive. It generates results quickly, leads to better comparability across studies, and can provide broad outlines of what variables are at play with what sorts of problems. That said, the anthropological concept of “culture” is hard to reduce to just one measure, for that misses the immersive, interactive, and shared dimensions of culture – the really operative parts of the concept.

    The problems here are very much like those facing complex trait genetics more generally. We won't get answers to many questions until we are able to look at much larger samples of people. And because the motivating factors for behavior are often very personal and local, we need to compare close relatives and members of individual communities on a massive scale.

    I am thinking explicitly about the "missing heritability" problem in human genetics. One solution to this problem is that the causal genes are rare, meaning that they can be most productively identified by comparing relatives to each other. Those relatives need to be embedded in large pedigrees for the comparisons to have any statistical power to test associations.

    Why should we expect studies of brain imaging to be any different? These studies are famously subject to the "dead fish" problem; small random differences between cases and controls show up as statistically important. Moreover, in small samples the appearance of correlations among uncorrelated variables creates a severe problem. The power to examine small differences between individuals randomly drawn from a population will be swamped out by variations throughout the brain. By comparing large sets of relatives, it may become possible to get some traction on the relationship of small brain differences and behavior. By looking within local communities in a stratified design, it should be possible for neuroscientists to pick apart the cultural influences on brain development from the genetic and individual influences. But there has been relatively little pedigree-based or community-based neuroimaging (much of it done on captive primates, not people).

    I raise this issue to reinforce what Lende has written about anthropology: These kinds of community-based and family-based approaches are naturals for anthropologists. And they provide a way for cultural neuroscientists to move beyond the "East versus West" comparisons of America and China, and move toward a much finer-grained understanding of how genetic and cultural levels of causation may interact within individuals.

    Synopsis: 
    Some thoughts on how to move forward the study of brain and culture
  • Keep still for your brain picture

    Thu, 2012-11-01 22:52 -- John Hawks

    Ben Deen and Kevin Pelphrey in Nature: "Perspective: Brain scans need a rethink" .

    Recent studies, however, have found that when a person moves their head while undergoing functional magnetic resonance imaging (fMRI) -- a method that maps how different neuroanatomical structures of the brain interact in real time, its functional connectivity -- it looks like the neural activity observed in autism. That's a sobering discovery: it means that a major source of evidence for a leading hypothesis on autism, and one that several research teams have pursued for years, may arise from an artifact.

    Remember the "dead salmon" study, in which inert tissue placed in the scanner produced results? The statistical methods underlying comparisons of fMRI between cases and controls rely on averaging a multidimensional space across many individuals. A bias doesn't have to be very large to lead to a significant difference between groups:

    [A]s one of the new studies showed, even a difference as small as 0.004 millimetre in average head motion across groups of patients can lead to significant differences in correlation strengths.

    That's four microns! That is, of course, an average across a large sample, each child has his or her own motion. Imagine trying to get them to average out so that the average motto is precisely equal across a few dozen individuals. And then, as the article discusses ways that might correct for linear biases, you are still left with the possibility that head motion has a nonlinear effect on result, so that the bias survives your attempt to correct for it.

    How remarkable, the very complex approaches necessary to deal with a relatively simple phenomenon.

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