Patients with autism may have altered visual processing; which could serve as an objective, nonverbal neural marker of the disorder, new research suggests. Using electroencephalography (EEG), investigators found that adults with autism have differences; in the part of the brain that processes visual information and these differences used to predict which individuals have autism.

“This signature of autism in vision seems to be a good objective neural marker of the condition in adults,” coinvestigator Caroline Robertson, PhD, assistant professor of psychological and brain sciences at Dartmouth College;Hanover, New Hampshire, and director of the Dartmouth Autism Research Initiative, told Medscape Medical News.  “Importantly, it does not require any verbal engagement from the individual; making it well-suited for future research with young preverbal kids and also nonverbal adults,” Robertson said.

“For a long time, they thought that autism was fundamentally about changes in regions of the brain; that process social information. Sensory symptoms have only recently recognized as core to autism,” Robertson explained. In earlier work, the investigators observed slower behaviorally reported rates of a basic visual phenomenon known as “binocular rivalry” in patients with autism.

Visual region of the brain

However, during binocular rivalry, two images one presented to each eye vie for awareness; alternating back and forth in perception. However, this competition relies in part on the balance of excitation and inhibition in the visual cortex; which may altered in autism. But until now, there was no direct neural evidence for this potential marker of excitation/inhibition (E/I) balance in autism, the researchers write.

Their latest study shows a “striking” alteration in the neural dynamics; of binocular rivalry in individuals with autism, they add. The study included 18 adults with autism and 19 age- and IQ-matched individuals to act as healthy controls. However, the investigators measured steady-state visually evoked potentials (VEP) via a single EEG electrode placed on a participant’s head over the visual region of the brain.

They were then presented with one of two visual images on a computer screen: red checkerboards in the left eye and green checkerboards in the right eye that flickered back and forth at different rates. The researchers replicated their prior findings of slower binocular rivalry; and reduced perceptual suppression in the patients with autism compared with controls. The results also provide “direct neural evidence” for slower rivalry in autism compared with the control group, they write.

Predict autism symptom

Using only the neural data from the visual test, they were able to predict autism symptom severity; and correctly classify individuals’ diagnostic status (autistic vs control) with 87% accuracy. “However, these findings clearly implicate atypical visual processing in the neurobiology of autism,” the researchers write. However, Robertson cautioned that although the findings allowed them to predict which adults; did vs did not have a diagnosis of autism, much work lies ahead.

“As a next step, they need to know if this difference in visual processing they identified in autism is specific to autism; as compared with other psychiatric conditions,” she said. To develop the measure as a screening tool for autism; it is also important to assess whether the results hold in younger, “ideally preverbal individuals,” she added. “However, in other words, can they predict which infants at risk for diagnoses of autism based on family history will go on to have a diagnosis based on early differences in visual processing? That’s currently an open question; but they are hopeful,” said Robertson.

“But as a diagnostic tool, I think it’s very hard to generalize what we see in this small sample to autism as a whole.” In addition, VEP can be done very quickly; provides an immediate response; and can used “in very low-functioning kids who do not follow instructions,” said Kolevzon. He noted that his personal belief about these kinds of tools is that they are going to be more informative in predicting; or monitoring treatment response because it will give a direct reflection of excitatory and inhibitory activity in the brain.