An EEG brainwave test gives researchers a way to identify children with autism more accurately, since evidence shows that their brains process sensory information like sight and sound differently than those of their peers.

Measuring how quickly the brain responds to sights and sounds could help doctors identify children at risk of developing autism, both earlier and more accurately. The new research is several years away from being used in the clinic, but researchers have shown that the social and communication difficulties displayed by children with autism correspond to specific, identifiable brainwave patterns.

The study, published today in the Journal of Autism and Developmental Disorders, is part of a push in the field of autism research toward identifying children at risk of autism earlier so that targeted treatments can be started at a younger age.

“One of the goals of research on autism is to develop biomarkers that can allow us to identify autism very early, perhaps before some of the behavioral symptoms that are characteristic of the disorder can be observed,” said Sophie Molholm, an associate professor of pediatrics and neuroscience at the Albert Einstein College of Medicine at Yeshiva University.

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Currently, autism spectrum disorder is diagnosed based on observations of a child’s behavior and symptoms, including how he or she interacts in certain environments. This approach tends to be very subjective and requires a clinician to have a great deal of experience.

Finding a more objective technique could allow doctors to not only identify children at risk of developing autism earlier, but also to better understand how severely they are affected — and to provide treatments targeted to their specific needs.

In an earlier study, Molhom and her colleagues found a link between brainwave patterns — as measured by an electroencephalogram (EEG) — and the severity of autism symptoms. In particular, children with autism processed multisensory information like sound, vision, and touch less quickly than typically developing children.

“We’ve demonstrated both behaviorally and through these neurophysiological measures that there are pretty profound differences in how information is processed and how it’s integrated,” Molhom said.

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The researchers built on this in the current study, presenting 43 autistic children, ages 6 to 17 years old, with a visual image, a simple auditory tone, or both combined. As children responded to the visual or auditory signals, researchers made continuous EEG recordings using electrodes attached to the scalp .

How quickly the children reacted to the auditory tone was strongly linked with the severity of their autism symptoms. Children with more severe autism took longer to process the auditory information, something seen in previous research.

There was also some connection, although not as strong, between how quickly children processed the combined audio-visual signal and the severity of their autism. Visual processing, however, showed no link to autism severity.

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More research is needed before this technique can be used in practice to identify children at risk of developing autism. This includes working with younger children.

“The hope is that [this technique] can really be used in conjunction with clinically-based diagnostics,” said Molholm, “but what you really want to be able to do is to use these for really early diagnosis — perhaps before the clinical symptoms are readily observable.”

The brain develops rapidly during infancy and some researchers feel that targeting children at risk of developing autism at this stage could prevent some of the social or communication changes that occur as the children age. One recent treatment targeted children as young as 6 months of age.

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Although the brainwave recordings have provided researchers with more insight into how the brains of children with autism respond to auditory and visual signals, Molholm doesn’t imagine that this technique will replace current methods of diagnosing children. Instead, it will add another layer of detail to the clinical picture.

“What you’re going to do is come up with a composite of metrics that allow you to confirm that they have the neural vulnerabilities, or processing differences, that define autism,” she said, “but it’s not going to be a single measure. It will be a number of measures put together.”

Molholm and her colleagues are continuing to collect brainwave data from children with autism and refining the measures that they will use to identify children at risk.

In addition to aiding diagnosis, this test could help researchers determine how effective treatment programs for autism are.

Molhom also hopes to use brainwave recordings to gain insight into the brains of children with lower IQ’s, “to really try and understand what’s going on there,” she said. “What are some of the strengths of these individuals that we might not be able to measure because they’re not as communicative, they’re not engaging, or responding to questions?”

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