Prefrontal cortex state representations shape human credit assignment

Abstract
Data availability
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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) state 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 predict credit assignment precision. Together this work provides a window into how neural representations drive adaptive learning.

Data availability

Behavioral data and analyzed neural data are available on github: https://github.com/amrita-lamba/eLife_prefrontal_credit_assignment. Model code and fMRI analysis scripts are also available on this repository.

The following data sets were generated

(2023) Prefrontal cortex state representations shape human credit assignment:
Behavioral data.

https://github.com/amrita-lamba/eLife_prefrontal_credit_assignment/tree/main/rl_pipeline_scripts
(2023) Prefrontal cortex state representations shape human credit assignment:
RSA data.

https://github.com/amrita-lamba/eLife_prefrontal_credit_assignment/tree/main/RSA_analysis_scripts
(2023) Prefrontal cortex state representations shape human credit assignment:
Parametric modulation analysis data.

https://github.com/amrita-lamba/eLife_prefrontal_credit_assignment/tree/main/pmod_analysis_scripts

Article and author information

Author details

Amrita Lamba

Department of Cognitive Linguistic and Psychological Sc, Brown University, Providence, United States

Competing interests
The authors declare that no competing interests exist.
Matthew R Nassar

2Department of Neuroscience, Brown University, Providence, United States

Competing interests
The authors declare that no competing interests exist.
Oriel FeldmanHall

Department of Cognitive Linguistic and Psychological Sc, Brown University, Providence, United States

For correspondence
oriel.feldmanhall@brown.edu

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-0726-3861

Funding

Brain and Behavior Research Foundation (26210)

Oriel FeldmanHall

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: Our study protocol was approved by Brown University's Institutional Review Board (Protocol #1607001555) and all participants indicated informed consent for both behavioral and neuroimaging portions of the study.

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.