EEG of infants brains may predict risk of autism, study says

From WebMD Health News:

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.

Autism is typically diagnosed through extensive behavioral testing at 2-3 years of age.

In the study, published in BMC Medicine, researchers compared EEGs from 79 infants aged 6 to 24 months. Forty-six of the infants were considered at high risk for autism because they had an older sibling with the behavioral disorder.

The babies wore helmet-like caps studded with electrodes on their scalps to measure electrical activity while they watched a research assistant blowing bubbles. The tests were repeated, when possible, at 6, 9, 12, 18, and 24 months of age.

The EEGs were then interpreted using modified multiscale entropy (mMSE), which measures the randomness of a signal.

The results showed that the greatest difference in brain activity patterns between the high-risk group and the comparison group of infants was at 9 months of age.

But there was a gender difference that researchers say they can't yet explain. The method's accuracy at picking out babies at risk for autism was greatest for girls at 6 months and for boys at 12 and 18 months.

Researchers say patterns in brain electrical activity can give many clues about how the brain is wired and how the connections between neurons in each part of the brain are functioning and organized.

“Many neuroscientists believe that autism reflects a ‘disconnection syndrome,’ by which distributed populations of neurons fail to communicate efficiently with one another,” says researcher Charles A. Nelson, PhD, research director of the Developmental Medicine Center at Children's Hospital Boston, in the release. “The current paper supports this hypothesis by suggesting that the brains of infants at high risk for developing autism exhibit different patterns of neural connectivity.”