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Using AI to Study Autism 

New discoveries published by BC researchers could help identify causes of Autism Spectrum Disorder, and lead to personalized interventions. 

Differences in behavior among people with Autism Spectrum Disorder (ASD) are closely related to differences in neuroanatomy—the shape of a brain—a team of Boston College neuroscientists reported in a recent issue of the journal Science. This discovery could aid in understanding the causes of ASD, and in developing personalized treatments.

The BC researchers used artificial intelligence to study MRI data from over one thousand individuals with ASD and compared those images to simulations of what the brains would look like if they did not have ASD. “We found that different people with ASD can have different brain areas affected, and thanks to the AI-simulated brains, we were able to identify which specific brain regions vary among ASD individuals,” said Aidas Aglinskas, a Boston College post-doctoral researcher and coauthor of the report. “In addition, separating ASD-related variation in brain anatomy from unrelated variation revealed hidden relationships between individual differences in brain anatomy and symptoms.”

Autism differs—both in symptoms and neuroanatomy—from one individual to another. Prior research has hypothesized that there might not be a single set of neuroanatomical characteristics common to all individuals with ASD. Confirming those suggestions has been difficult because identifying ASD-specific neural alterations is a challenging task, said Aglinskas,  who conducted the research with BC Assistant Professors of Neuroscience Joshua Hartshorne and Stefano Anzellotti. Brains are different due to many factors, including genetic variation not due to ASD, which is hard to control for in a research study.

That’s why the team turned to AI to identify patterns of neural variability that are ASD-specific and to determine whether these ASD-specific features of brain anatomy vary across individuals in a way that relates to their symptoms. To create the simulations of what each individual’s brain would look like if they did not have ASD, the team employed a novel AI technique that separates individual differences in brain anatomy into ASD-specific and ASD-unrelated features. “We were surprised to find that, despite observing a large amount of variation in brain anatomy between ASD individuals along multiple dimensions, individuals did not group into distinct, categorical subtypes as previously thought,” Aglinskas said.

Moving forward, the researchers point to a need to understand in more detail how these neuroanatomical differences affect behavior. Anzellotti said they plan to use the AI tools to look beyond brain structure for ways to better understand ASD diagnoses and the behavior of individuals with ASD. “Two brains can be shaped very similarly but still work differently,” Anzellotti said. “There are a number of other aspects of the brain we will need to look at to get a full picture. Right now, we are focused on functional connectivity—a measure of how the brain is wired. A big question is whether that will show us something new about individual differences within ASD. The goal of this type of work is to be able to use brain imaging data to aid in developing personalized healthcare approaches for those with ASD.” 

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