MIT Study Presents New Theory on Autism

The study says the disorder may be related to difficulty guessing outcomes and actions.

If you saw someone yawning at a party, you’d likely assume they were tired and ready to leave. But for individuals with autism, that connection may not be so easily made, according to a new study by researchers at MIT. The research says that could stem from a difficulty “predicting” outcomes and actions—in other words, a difficulty reading a situation to guess what will come next and how they should react.

While no one is truly able to predict what’s coming, the study’s lead author Pawan Sinha, a professor of neuroscience at MIT, points out that daily activities like a simple conversation do rely heavily on using context and past experience to make an educated guess about the outcome.

“Communication and the choreography of social interactions depend crucially on the ability to learn how one event predicts another—a shrug of the shoulders and lowered tone suggesting the imminent end of remarks, or a sideways glance suggesting boredom,” explains Sinha. After studying a wide range of autism symptoms—including difficulty understanding social situations, repetitive behaviors, and sensory sensitivity—Sinha and his team concluded that they all may be linked to not having that ability to guess what’s to come.

“Many caregivers report that children with autism require a structured environment. This is another way of saying that the environment needs to be highly predictable,” Sinha says. “The fact that even slight deviations from such predictability can prove very distressing to those on the autism spectrum pointed us towards the possibility that autism might be associated with a reduced predictive ability.”

But Arshya Vahabzadeh, an autism expert who specializes in child and adolescent psychiatry at MGH, isn’t so sure. Vahabzadeh says that the problem may not be that those with autism cannot use information to make logical assumptions, but that they may not even be taking the same information from social situations—like noticing unfocused eyes or negative body language—as people without autism.

“I would be cautious of saying that we’ve got two sets of individuals who both have the same sets of data, but one set just can’t utilize the data to predict out the same thing as the other group,” Vahabzadeh says. “I’m not sure that people with autism actually even have access to the same data.”

Vahabzadeh also says that the wide ranging autism spectrum makes it difficult to make broad conclusions about the disorder—a fact that Sinha also acknowledges, noting that the team plans to look into their theory much further. “The question that these challenges pose is whether there is a common underlying thread that connects the different traits and the different individuals,” Sinha says, “or are they so disparate that we cannot expect there to be an overarching explanation?”

Though it may not be possible to answer that question right now, Vahabzadeh says research like MIT’s is crucial to moving the medical community in that direction. “I think putting out new theories is actually very important to advance the field,” he says. “It gives us a chance to do more novel experiments, because the worst thing that can happen is we’re right or wrong. We don’t lose anything by testing out new ideas.”