Work

Prefrontal cortex state representations shape human credit assignment

Year: 2023

Type: article

Abstract: People learn adaptively from feedback, but the rate of such learning differs drastically across individuals and contexts. Here we examine whether this variability reflects differences in what is learned. Leveraging a neurocomputational approach that merges fMRI and an iterative reward learning task, we link the specificity of credit assignment—how well people are able to appropriately attribute outcomes to their causes—to the precision of neural codes in the prefrontal cortex (PFC). Participants credit task-relevant cues more precisely in social compared to nonsocial contexts, a process that is mediated by high-fidelity (i.e., distinct and consistent) neural representations in the PFC. Specifically, the medial PFC and orbitofrontal cortex work in concert to match the neural codes from feedback to those at choice, and the strength of these common neural codes determines learning success. Together this work provides a window into how neural representations drive adaptive learning.

Source: eLife

DOI: 10.7554/elife.84888

Authors: Amrita Lamba, Matt R. Nassar, Oriel FeldmanHall

Institution: Brown University

Language: English

Topic: Neural and Behavioral Psychology Studies

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $2,500

Funders: Brain and Behavior Research Foundation, National Alliance for Research on Schizophrenia and Depression, National Institute of Mental Health