Marvin Chun, PhD

My laboratory employs functional magnetic resonance imaging (fMRI) to study visual attention, memory, decision-making, perception, and performance. One focus is to use fMRI to decode brain activity to understand how people perceive, remember, and make decisions. For example, we can read out which faces people are viewing in the scanner, or determine whether people are attentive or distracted. Another goal is to use fMRI to measure individual differences in behavior. Can we use fMRI to predict how well people will perform a task, even when people aren't doing anything while being scanned?

behavioral testing ;  computational modeling ;  deep learning ;  functional magnetic resonance imaging ;  network analysis ;  neural networks ;  pattern classification ;  psychophysics  

artificial intelligence ;  attention ;  cognitive neuroscience ;  computational neuroscience ;  connectivity ;  predictive modeling ;  working memory ;  network neuroscience  

Marvin Chun received his B.A. in Psychology from Yonsei University, his Ph.D. in Brain and Cognitive Sciences from the Massachusetts Institute of Technology, and his postdoctoral training at Harvard University. At Yale, he is the Richard M. Colgate Professor of Psychology, and he has secondary appointments in the Department of Neuroscience at the Yale School of Medicine and the Cognitive Science Program in Yale College. His partner Woo-kyoung Ahn is also a Professor of Psychology at Yale.