Frontostriatal interactions in working memory and reinforcement learning

Summary

Date: 
October 9, 2018 - 12:00pm
Location: 
BioLabs Building, Room 1080
About the Speaker
Name: 
Michael Frank
Speaker Title: 
Professor
Speaker Affiliation: 
Brown University

Behavioral learning should be compared to a symphony, rather than to a violin solo: many different neurocognitive players contribute to various aspects of learning, which may be differentially engaged depending on task demands. While many studies implicate altered reward learning in patients populations, parsing out the underlying mechanisms requires one to reliably attribute different aspects of their behavior to the relevant player, and to understand how dysfunction in one player may impact the others. I will show how combining targeted experimental design and computational modeling approaches can allow us to disentangle the contributions some of these players, focusing on striatal reward-based learning, prefrontal working memory / cognitive control components, and their interactions. We leverage methods for extracting trial-by-trial indices of reinforcement learning (RL) and working memory (WM) in human electro-encephalography to reveal single-trial computations beyond that afforded by behavior alone. This method provides constraints on the nature of interactions among systems and has also shed light on the mechanisms underlying reward learning deficits in schizophrenia.