This is a brain model with regions of interest highlighted. Photo courtesy of University of Warwick.
March 23, 2015 — The functional differences between autistic and non-autistic brains have been isolated for the first time, following the development of a new methodology for analyzing magnetic resonance imaging (MRI) scans.
Developed by researchers at the University of Warwick, the methodology — called Brain-Wide Association Analysis (BWAS) — is the first capable of creating panoramic views of the whole brain and provides scientists with an accurate 3-D model to study.
The researchers used BWAS to identify regions of the brain that may make a major contribution to the symptoms of autism.
BWAS does so by analyzing 1,134,570,430 individual pieces of data — covering the 47,636 different areas of the brain — called voxels, which comprise a functional MRI (fMRI) scan and the connections between them.
Previous methodologies were unable to process this level of data and were restricted to modeling only limited areas.
The ability to analyze the entire dataset from an fMRI scan provided the Warwick researchers the opportunity to compile, compare and contrast accurate computer models for both autistic and non-autistic brains.
Led by BWAS developer Prof. Jianfeng Feng, from the University of Warwick's Department of Computer Science, the researchers collected the data from hundreds of fMRI scans of autistic and non-autistic brains.
By comparing the two subsequent models, the researchers isolated 20 examples of difference, where the connections between voxels of the autistic brain were stronger or weaker than the non-autistic.
The identified differences include key systems involved with brain functions relating to autism. Feng explained the findings:
"We identified in the autistic model a key system in the temporal lobe visual cortex with reduced cortical functional connectivity. This region is involved with the face expression processing involved in social behavior. This key system has reduced functional connectivity with the ventromedial prefrontal cortex, which is implicated in emotion and social communication."
The researchers also identified in autism a second key system relating to reduced cortical functional connectivity, a part of the parietal lobe implicated in spatial functions.
They propose that these two types of functionality — face expression-related, and of one's self and the environment — are important components of the computations involved in theory of mind, whether of oneself or of others, and that reduced connectivity within and between these regions may make a major contribution to the symptoms of autism.
The researchers argue that the methodology can potentially isolate the areas of the brain involved with other cognitive problems, including obsessive compulsive disorder, ADHD and schizophrenia.
By using meta-analysis and a rigorous statistics approach the Warwick researchers were able to collect and use a big dataset to obtain significant results, the likes of which have not been seen in autistic literature before. Professor Feng explains:
"We used BWAS to analyze resting state fMRI data collected from 523 autistic people and 452 controls. The amount of data analyzed helped to achieve the sufficient statistical power necessary for this first voxel-based comparison of whole autistic and non-autistic brains. Until the development of BWAS this had not been possible.
"BWAS tests for differences between patients and controls in the connectivity of every pair of voxels at a whole brain level. Unlike previous seed-based or independent components-based approaches, this method has the great advantage of being fully unbiased in that the connectivity of all brain voxels can be compared, not just selected brain regions."
The research, published in the journal Brain, is titled “Autism: Reduced Connectivity between Cortical Areas Involved with Face Expression, Theory of Mind, and the Sense of Self.”
For more information: www.warwick.ac.uk