ResearchBlogging.org

Major brain structures implicated in autism.
Image via Wikipedia

Autism is a spectrum disorder , better referred to as ASD, It has been known for some time that differences like autism are, multi-dimensional and not readily reducible to a single set of mechanisms or genetic causes. In the past we have discussed how the disorder may be related to structural differences in the brain like those due to minicolumnar differences.

A new study looked at structural differences in brains of people (adults) with ASD and instead of focusing piece-meal on one feature (like minicolumns) combined a multitude of structural features and used a multi-dimensional classification system to determine the accuracy and specificity of the structural differences to predict/aid in  diagnoses.

They came uyp with five dimensions- two based on volumetric measurements (surface area and cortical thickness) and the other three on geometric features (average convexity/concavity, mean radial curvature and metric distortion.  (the article is open access, so go read it to find what these mean:-) )

What they found was that cortical thickness was the strongest predictor and that predictive power was greater for Left hemisphere measures than for right hemisphere measures.

They also talk about what these measures may mean in terms of underlying neurons and substructures and I reproduce that here:

There is already evidence to suggest that several aspects of cerebral morphology are different in people with ASD—including both volumetric (i.e., cortical thickness, regional area) and geometric (i.e., cortical shape) features (Levitt et al., 2003; Nordahl et al., 2007); and that different morphological features may have different neuropathological and genetic underpinnings (Panizzon et al., 2009). For instance, cortical thickness is likely to reflect dendritic arborization (Huttenlocher, 1990), while cortical surface area has been linked to the number of minicolumns in the cortical layer (Rakic, 1988). Geometric features such as cortical folding pattern, on the other hand, may reflect an abnormal pattern of intrinsic as well as extrinsic connectivity (Van Essen, 1997). Thus, examining the relationship between such multiple cortical features could provide invaluable insights into the multifactorial etiology of ASD.

We know form previous work that all of the above (arborization, minicolumns, local and global connectivity) have been implicated in Autism. The important take-home for me from thi sstudy is the fact that all these are governed by possibly separate underlying genetic mechanisms and may thus be independent of each other. On its own variations in one dimension may not lead to full blown autism, but when variations in all five or more dimensions combine they may make one more susceptible to ASD diagnosis.

Remember we are only talking about structural change sin brains here; we haven’t even touched upon functional differences (default mode network?) and there is plethora of evidence that functional changes are also very important. Overall I believe the multi-dimensional nature of underlying structural and functional differences lend autism the spectrum property and also a continuum with normality. As always I would be eager to know how the SVM they used to classify Autistics fared when asked to classify Psychotics …did the pattern they see was reverse of Autism and inline with the Schizophrenia/psychosis as opposed to Autism theory?

Enhanced by Zemanta

Ecker, C., Marquand, A., Mourao-Miranda, J., Johnston, P., Daly, E., Brammer, M., Maltezos, S., Murphy, C., Robertson, D., Williams, S., & Murphy, D. (2010). Describing the Brain in Autism in Five Dimensions–Magnetic Resonance Imaging-Assisted Diagnosis of Autism Spectrum Disorder Using a Multiparameter Classification Approach Journal of Neuroscience, 30 (32), 10612-10623 DOI: 10.1523/JNEUROSCI.5413-09.2010

GD Star Rating
loading...

Effecient Related Posts: