Apart from this brief mention on Amanda's blog, I hadn't read anything at the time about the new multidimensional brain scan described last month in the Journal of Neuroscience. I was intrigued, because one thing that's been awfully elusive to autism researchers is a consistent, reproducible biological marker that's specific to autism.
[R]eports of region-specific differences in ASD are highly variable [for review, see Toal et al. (2005) and Amaral et al. (2008)]. Such variable findings may simply be explained by confounds such as clinical heterogeneity between studies, or analytical techniques. Alternatively, variability in findings may indicate that differences in brain anatomy in ASD are relatively subtle and spatially distributed, and are difficult to detect using mass-univariate (i.e., voxelwise) approaches. Last, given the multiple etiology of ASD, it is likely that its neuroanatomy is not confined to a single morphological parameter but affects multiple cortical features.
Here's a classification plot showing the two categories as determined by applying the five-variable classifier to the left hemisphere:
Here, all but two autistic subjects are placed into the positive (i.e., autistic) category, and all but four control subjects are correctly placed into the negative category.
--- where you see a lot more crossover between categories, plus several subjects straddling the border line. It is also only in the left hemisphere that any correlation is observed between how far to the right of the dividing line a person is and their ADI scores in the social and communication domains.
Some parameters also performed better than others: cortical thickness had the highest accuracy levels of any parameter (90% in the left hemisphere!), followed by metric distortion.
Finally, in the left hemisphere the model also succeeded in distinguishing ADHD subjects from autistic ones. (In the right hemisphere, it placed about equal numbers of ADHD subjects in each category). That's important because it shows that the model is actually picking up on characteristics of autistic brains, instead of just registering all deviance from "normal."
So, what *ARE* these characteristics of autistic brains? Well, they vary by region --- not only in terms of which parameter is relevant, but also in terms of how autistic people differ from neurotypicals on a given parameter.
For instance, if you look at this map of how the autistic subjects' brains differed from the controls in terms of cortical thickness, you can see that some parts of the brain (mostly on the temporal lobe) tend to have a thicker layer of gray matter in autistic people, while in other areas (mostly on the frontal and parietal lobes), the cortex tends to be thinner in autistic people.
Figure 4 (A), in Ecker et al. (2010); red areas represent more gray matter in relation to average non-autistic brain, blue areas represent less gray matter.
Some of the areas that showed up as having an "excess" of gray matter surprised me, as differential activity in those areas (fusiform gyrus, superior temporal sulcus) had previously been theorized to underlie autistic "deficits" in making sense of faces.
Besides these differences in amount of gray matter, there were also some strong differences in gray matter geometry: first, the autistic subjects showed greater sulcal depth in two regions --- the intraparietal sulcus and the superior frontal cortex --- and second, the inferior parietal lobes and certain regions in the right frontal lobe --- the right supramarginal gyrus, postcentral gyrus, and orbitofrontal cortex --- along with the precuneus, showed different patterns of cortical folding.
For example, here's the right intraparietal sulcus:
From Figure 5 (B), in Ecker et al. (2010)
The blue line represents the cortical surface for the average control subject; the red line represents the average autistic subject's cortex. You can see that the sulcus goes down deeper in the autistic subjects, and also that the gyri on either side are a bit steeper.
I would like to point out, again, that it's not necessarily any single variation at any one region of the brain that this statistical analysis has tied to autism, though --- it's a pattern of gray-matter distribution. It's also a pattern that's so far only been observed in a tiny, rather homogeneous sample of autistic men --- much larger, broader-based studies of this classifier need to be done to see if the same patterns hold up for all of the people currently lumped together under the category "autistic," or whether separate neuroanatomical phenotypes will define autistic subtypes.
I would also like to see future studies done using different diagnostic tools to define the autistic group --- if the goal of this research is to establish a biomarker for autism diagnosis so that we can finally be done with frustratingly ambiguous diagnosing-from-behavior, it will hardly do to have the biomarker be dependent on one of the older behavioral diagnostic tools for its template!
*According to this table showing demographic data on the autistic and control (but not the ADHD) subjects, the autistic subjects were mostly young, and some middle-aged, men (the average age (33) was much closer to the age of the youngest person (20) than it was to that of the oldest person (69)) and had a very wide range of IQ scores as measured by the Weschler Abbreviated Scale of Intelligence. The standard deviation, for full-scale IQ and for verbal and performance IQ, was around 20 points for the autistic group, and scores ranged from 76 (just one point over the cutoff point the authors chose to designate intellectual disability, which is a full-scale IQ of 75) to 141, with verbal IQs ranging from 78 to 133 and performance IQs from 77 to 138. These subjects, I'd like to point out in the spirit of adding to Michelle Dawson's recent post on functioning levels, were all defined as having Asperger's or high-functioning autism.
Ecker C, Marquand A, Mourão-Miranda J, Johnston P, Daly EM, Brammer MJ, Maltezos S, Murphy CM, Robertson D, Williams SC, & Murphy DG (2010). Describing the brain in autism in five dimensions--magnetic resonance imaging-assisted diagnosis of autism spectrum disorder using a multiparameter classification approach. The Journal of neuroscience : the official journal of the Society for Neuroscience, 30 (32), 10612-23 PMID: 20702694