Head motions offer better way to detect autism in girls
OREANDA-NEWS Tracking and measuring the involuntary head movements revealed in functional magnetic resonance imaging (fMRI) scans could be a more accurate method of detecting autism in girls, new research suggests.
“The criteria are male-driven, so we’re measuring females with a male ruler.”
Neuroscientist Elizabeth Torres of Rutgers University-New Brunswick says the traditional criteria used to diagnose autism are largely based on the observed behavior of children, and since boys in western society are expected to be active, deviations from that norm are easy to spot. Girls are socialized to be quieter, so autism is harder to observe. Perhaps partly due to these cultural biases, boys are diagnosed with autism five times as often as girls.
“The criteria are male-driven, so we’re measuring females with a male ruler,” she says.
In a new paper, which appears in the journal Frontiers in Integrative Neuroscience, Torres and her coauthors report on what they found by matching data about involuntary head movements from fMRI scans to diagnoses of autism spectrum disorder.
“When you go in an fMRI machine, they tell you to hold still,” she says. “But you can’t hold totally still; nobody can. The machine will pick up involuntary movements that the patient is unaware of and that an observer wouldn’t see with the naked eye.”
Torres, associate professor of psychology in the School of Arts and Sciences, used data from the Autism Brain Imaging Data Exchange (ABIDE) databases, which contain raw information from brain scans collected from laboratories around the world—a guard against the cultural bias inherent in observation.
Torres says the tools traditionally used to diagnose autism offer no definition of “normal” behavior, nor do they offer standardized scales that can be mapped to the kind of neurophysiological data that comes from fMRI scans. Involuntary motions, however, like those measured by fMRI scans, may help clinicians more accurately determine whether and where a person belongs on the autism spectrum.
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