New research suggests that a simple, inexpensive test may be able to accurately identify whether or not children as young as 3 months will go on to have autism.

A study published online this week in the journal Scientific Reports found that the developmental disorder can be flagged in infants by measuring electrical activity in the brain using an electroencephalogram, or EEG.

The test was able to pick up on autism in some babies by 3 months and had near-perfect accuracy by 9 months.

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“EEGs are low-cost, non-invasive and relatively easy to incorporate into well-baby checkups,” said Charles Nelson, director of the Laboratories of Cognitive Neuroscience at Boston Children’s Hospital and a co-author of the study. “Their reliability in predicting whether a child will develop autism raises the possibility of intervening very early, well before clear behavioral symptoms emerge. This could lead to better outcomes and perhaps even prevent some of the behaviors associated with ASD.”

The study looked at 99 children considered to be at high risk for autism because they had an older sibling with the condition as well as 89 low-risk kids. All of the participants had EEGs at ages 3, 6, 9, 12, 18, 24 and 36 months and they took part in a traditional behavioral evaluation for autism.

Using computational algorithms, researchers assessed six different frequencies of the EEGs and were able to offer a “highly accurate” prediction of autism risk at just 3 months.

“The results were stunning,” said William Bosl, an associate professor of health informatics and clinical psychology at the University of San Francisco who worked on the study. “Our predictive accuracy by 9 months of age was nearly 100 percent. We were also able to predict ASD severity, as indicated by the (Autism Diagnostic Observation Schedule) Calibrated Severity Score, with quite high reliability, also by 9 months of age.”

Those behind the study said that additional research on a larger and more diverse population of children is needed to determine if the EEG approach would be an effective way to detect autism in clinical settings.