There are various differences between typically developing children and children on the autism spectrum. To investigate that, Northeastern’s Matthew Goodwin and the MIT Media Lab will collaborate on a study looking at behavioral, physiological, emotional, and social differences between groups of children with autism diagnoses and children not on the spectrum. The children will interact with their parents during the study.
The study is funded by the Simons Center for the Social Brain at MIT, which offers seed grants of up to $150,000 in direct costs to new collaborations between Boston-area labs. Goodwin, an interdisciplinary assistant professor in health science at Bouvé and computer science at CCIS, is working with Rosalind Picard, who directs the Affective Computing Research Group at MIT’s Media Lab. Goodwin is also director of the Computational Behavioral Science Laboratory at Northeastern, and a visiting professor at the Media Lab. Oliver Wilder-Smith, a doctoral student under Goodwin, and Jillian Sullivan, a postdoc working in Goodwin’s lab, will also be part of the collaborative study. Goodwin and Picard’s labs were awarded $149,720, which they will receive starting on Jan. 1, 2016.
“In this project we seek to evaluate biological markers of social reciprocity and emotion regulation in very young kids at risk for or who have recently been diagnosed with autism,” Goodwin, who has collected psychophysiological data from children with autism throughout his career, says. “This will be the first time that I have a dedicated project to systematically collect information about physiologies from two people simultaneously and model it within autism.”
The study will use a toy platform developed by Kristy Johnson, who used to work with Goodwin at Northeastern as a research associate and is currently a grad student under Picard at the Media Lab. How children interact with the toy will be used to investigate emotional regulation and the social dynamics between a child and their parent.
Johnson’s four-year-old son, Felix, has a rare genetic disorder and an autism diagnosis. Watching his difficulties tackling tasks and activities most children do naturally prompted Johnson to develop an interactive toy platform that she hopes will engage children with neuro-differences, like autism.
“Playing is not fun for him,” Johnson says of Felix. “Playing is hard for him. The effort level is at a 10 and the interest level is at a 2. Studies have shown that children actually learn better when the level of the task is matched to what motivates them.”
The toy is a wooden hexagon with three legs and different technologies like LED lights, music, and video clips built into it, which can be programmed to give children personalized rewards for different goals. The study involves five steps that test how a child responds to various scenarios involving the toy, including when the toy is turned off; when it is turned on and provides regular rewards for completed tasks; when rewards aren’t always provided consistently; and when the child needs to ask their parent for help to complete the task. Throughout the study, the parent and child pair will wear wireless biosensors to track physiological responses to the different tasks, and will also be videoed to record the interactions between the two.
The data Goodwin hopes to collect will provide information about coordinated behavior, social reciprocity, and emotional regulation in children with autism and children not on the spectrum. This data will be based on how the children interact with the toy and with their parent.
Goodwin hypothesizes there will be identifiable physiological differences between parent and child dyads in the autism group, and that those differences won’t be observed in the typical development group. “That’s a potentially valuable biomarker that could be used in future research for screening, diagnosis, and response to intervention,” he says. Goodwin also predicts that children with more severe forms of autism will experience greater physiological dysregulation than those who are mildly affected.
And hopefully, Felix will enjoy playing with the toy platform his mother has developed. “I wanted to design a tool that could match the reward to the challenge, and see if that was able to help him learn,” Johnson says. “This was all motivated by my son.”