Research

“Social” or “Emotional”?

Many families of neurotypical and neurodivergent children wonder if their child’s social challenges could be related to anxiety, depression, or differences in social communication abilities. The NIH-funded Adolescent Communication of Emotion Study (ACES) is a collaboration between scientists at CHOP, Penn, and the Baylor College of Medicine (Eric Storch, PhD) that seeks to develop new measures that can track similarities and differences between social and emotional challenges. Unlike most traditional measures that rely on self or parent report, this study uses cutting-edge computer vision and computational linguististics to characterize live social interactions in terms of socio-emotional content. In addition to developing new measures, this grant is designed to answer basic questions about the extent to which what we think of as “social” and “emotional” constructs are actually different from one another - which may in turn influence how we define autism in the future. This study is currently enrolling 12 to 17 year-olds with and without mental health concerns (i.e., autism, anxiety, and depression). Click here if you would like more information about participating.

Waves of Emotion

Most children experience an ever-changing repertoire of emotions. It is therefore surprising how little we know about how much emotion variability is typical for a school-age child, and whether this might be different for neurodivergent children. The Eagles Autism Variability of Emotion (EAVE) study, funded by the Philadelphia Eagles Autism Foundation, uses techniques from psychophysiology, computer vision, and experience sampling to track variability in emotional experiences among autistic children and adolescents. The goal of this research is to identify the extent to which emotions are variable across time and contexts (in the lab, and at home).

The Ethics of Digital Phenotyping

Computer vision, machine learning, and artificial intelligence are providing exciting new tools that are poised to revolutionize how we understand and track mental health. Many of these new “digital phenotyping” tools record language, behavior, and physiological activity passively, without any particular effort from those being studied. These tools raise ethical concerns that are best identified before these tools are integrated into standard clinical practice. Led by Kristin Kostic Quenet, Eric Storch (both at Baylor College of Medicine), and John Herrington, this project uses qualitative methods to survey children, parents, professionals and scholars regarding their most pressing concerns about these new technologies. A key goal of this research is to provide ethical guidelines for scientists developing digital phenotyping tools, and for clinicians who include them in their practices.

The Cognitive Neuroscience of Emotion in Autism

Decades of cognitive neuroscience research have identified brain structures and networks that are related to the core features of autism. However, many of these same structures and networks have also been associated with mood and anxiety disorders (for example, amygdala and portions of prefrontal cortex). By identifying unique and overlapping neural signals of autism, anxiety, and depression, we may not only come up with a clearer picture of the etiology of autism, but also better understand the extent to which emotion processes ought to be considered fundamental to the autism diagnosis itself.