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Last updated on April 18, 2014 at 21:21 EDT

Autistic Brains Create 42 Percent More Information During Rest: Study

January 31, 2014
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Lee Rannals for redOrbit.com – Your Universe Online

A new study published in the journal Frontiers in Neuroinformatics shows that autistic brains can create 42 percent more information on average while at rest.

The research, performed by Case Western Reserve University and University of Toronto neuroscientists, could explain an autistic child’s detachment from his/her environment.

“Our results suggest that autistic children are not interested in social interactions because their brains generate more information at rest, which we interpret as more introspection in line with early descriptions of the disorder,” Roberto Fernández Galán, PhD, senior author and associate professor of neurosciences at Case Western Reserve School of Medicine, said in a statement.

Researchers used magnetoencephalography (MEG) to record brain activity of autistic children, revealing that their brains at rest generate more information than non-autistic children. They also quantified interactions between brain regions and determined the inputs to the brain in the resting state allowed them to interpret the children’s introspection level. The team believes this finding could explain an autistic child’s lack of interest in external stimuli, such as interactions with other people.

“This is a novel interpretation because it is a different attempt to understand the children’s cognition by analyzing their brain activity,” José L. Pérez Velázquez, PhD, first author and professor of neuroscience at University of Toronto Institute of Medical Science and Department of Pediatrics, Brain and Behavior Center, said in a statement. “Measuring cognitive processes is not trivial; yet, our findings indicate that this can be done to some extent with well-established mathematical tools from physics and engineering.”

This study is a follow-up to a previous finding by the same team in which they were able to develop a method to help detect autism in children. The team used MEGs and analyzed dynamic patterns in brain activity to determine the brain’s functional connectivity, which is the communication from one region to another. They were able to detect autism spectrum disorder with 94 percent accuracy using this method.

“We asked the question, ‘Can you distinguish an autistic brain from a non-autistic brain simply by looking at the patterns of neural activity?’ and indeed, you can,” Galán said about the April 2013 study. “This discovery opens the door to quantitative tools that complement the existing diagnostic tools for autism based on behavioral tests.”


Source: Lee Rannals for redOrbit.com - Your Universe Online