Combining a standard noninvasive test that measures electrical activity in the brain with a high-tech computer analysis may help determine the risk of autism spectrum disorder in infants, according to a new study.
In the study, a computer program that assists in evaluating brainwave data from an electroencephalogram (EEG) was used to determine the way nerve cells communicate with one another in infants. Using the data generated, researchers were able to predict which 9-month-old infants have a high risk of autism with 80% accuracy.
“Electrical activity produced by the brain has a lot more information than we realized,” says researcher William Bosl, PhD, of Children’s Hospital Boston, in a news release. “Computer algorithms can pick out patterns in those squiggly lines that the eye can’t see.”
These results are only preliminary, but researchers say the technique could lead to less invasive and much earlier determination of autism risk by picking up subtle differences in brain organization and activity.
Full story: Electrical brain activity may spot autism risk