ScienceDaily (2011-02-22) — A computational physicist and a cognitive neuroscientist have come up with the beginnings of a noninvasive test to evaluate an infant’s autism risk.

It combines the standard electroencephalogram (EEG), which records electrical activity in the brain, with machine-learning algorithms. In a pilot study, their system had 80 percent accuracy in distinguishing between 9-month-old infants known to be at high risk for autism from controls of the same age.