Ted Satterthwaite

McLure Associate Professor in Psychiatry and Behavioral Research
University of Pennsylvania

Ted Satterthwaite is McLure Associate Professor in Psychiatry and Behavioral Research at the University of Pennsylvania’s Perelman School of Medicine. He completed medical and graduate training at Washington University in St. Louis, where he was a student of Randy L. Buckner. Subsequently, he was a psychiatry resident and a neuropsychiatry fellow at Penn, under the mentorship of Raquel E. Gur. He joined the faculty of the psychiatry department in 2014 and served as director of imaging analytics at the Brain Behavior Laboratory from 2015 to 2019. Since 2020, he has directed the Penn Lifespan Informatics and Neuroimaging Center. His research uses multi-modal neuroimaging to describe both normal and abnormal patterns of brain development, in order to better understand the origins of neuropsychiatric illness. He has been the principal investigator on nine R01 grants from the National Institutes of Health. His work has been recognized with the Brain and Behavior Research Foundation’s Klerman Prize for Clinical Research, the NIMH Biobehavioral Research Award for Innovative New Scientists (BRAINS) award, the NIH Merit Award, as well as several teaching awards.

From this contributor

Explore more from The Transmitter

Clockwise: lab mouse, zebrafish, octopus, rat pushing a cube, nematodes, fruit fly.

The term ‘model organism’ should be reserved for biological systems

By referring to artificial neural networks as model organisms, we run the risk of distorting funding priorities and disregard the explanatory power of a shared evolutionary history across biological organisms.

By Marc Coutanche
13 November 2026 | 6 min read

New phase of BRAIN Initiative spawns basal ganglia ‘parts list’

With a standardized cell naming system and infrastructure for data collection and analysis, the basal ganglia project sets the stage for a whole-brain primate atlas.

By Claudia López Lloreda
12 November 2026 | 1 min watch
Research image showing genes containing microexons in mice.

Machine-learning model spots autism-linked variants that scramble splicing

The model provides a way to investigate genetic variation in regions of the genome whose functions have been difficult to interpret.

By Giorgia Guglielmi
12 November 2026 | 4 min read