In an ancient Indian parable, a group of blind men touches different parts of a large animal to find what it is. Only when they share the descriptions of an ear, tail, trunk and leg do they know it is an elephant.
Rajesh Kana, Ph.D., of the University of Alabama at Birmingham has brought a similar approach to the classification, and eventual diagnosis, of autism. Kana and colleagues are the first to combine three different measures of the brain — anatomy, the connectivity between different brain regions, and levels of a neurochemical — to distinguish people with autism spectrum disorder (ASD) from matched, typically developing peers. This multimodal approach, published online this week in the journal “Cortex,” is distinct from many previous studies that have used a single neuroimaging measure. While those studies uncovered widespread functional and anatomical brain abnormalities in ASD, the results were not highly consistent, possibly reflecting the complex brain pathology in autism spectrum disorders.
At this time, autism diagnosis is based on behavior. Kana’s multimodal neuroimaging-based classification is a step toward a possible biomarker for autism and possibly diagnosing autism at an early age, perhaps as early as 6 months, when the brain is very plastic and intervention might be more effective. “But that’s a long, long way off,” said Kana, an associate professor in the Department of Psychology in the UAB College of Arts and Sciences and an associate scientist in UAB’s Civitan International Research Center.
Read the entire UAB news release HERE
