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Executive Function Assigns Value to Novel Goal-Congruent Outcomes

Overview
Journal Cereb Cortex
Specialty Neurology
Date 2021 Jul 7
PMID 34231854
Citations 5
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Abstract

People often learn from the outcomes of their actions, even when these outcomes do not involve material rewards or punishments. How does our brain provide this flexibility? We combined behavior, computational modeling, and functional neuroimaging to probe whether learning from abstract novel outcomes harnesses the same circuitry that supports learning from familiar secondary reinforcers. Behavior and neuroimaging revealed that novel images can act as a substitute for rewards during instrumental learning, producing reliable reward-like signals in dopaminergic circuits. Moreover, we found evidence that prefrontal correlates of executive control may play a role in shaping flexible responses in reward circuits. These results suggest that learning from novel outcomes is supported by an interplay between high-level representations in prefrontal cortex and low-level responses in subcortical reward circuits. This interaction may allow for human reinforcement learning over arbitrarily abstract reward functions.

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References
1.
Esteban O, Markiewicz C, Blair R, Moodie C, Isik A, Erramuzpe A . fMRIPrep: a robust preprocessing pipeline for functional MRI. Nat Methods. 2018; 16(1):111-116. PMC: 6319393. DOI: 10.1038/s41592-018-0235-4. View

2.
Howard J, Gottfried J, Tobler P, Kahnt T . Identity-specific coding of future rewards in the human orbitofrontal cortex. Proc Natl Acad Sci U S A. 2015; 112(16):5195-200. PMC: 4413264. DOI: 10.1073/pnas.1503550112. View

3.
McDougle S, Butcher P, Parvin D, Mushtaq F, Niv Y, Ivry R . Neural Signatures of Prediction Errors in a Decision-Making Task Are Modulated by Action Execution Failures. Curr Biol. 2019; 29(10):1606-1613.e5. PMC: 6535105. DOI: 10.1016/j.cub.2019.04.011. View

4.
Collins A, Brown J, Gold J, Waltz J, Frank M . Working memory contributions to reinforcement learning impairments in schizophrenia. J Neurosci. 2014; 34(41):13747-56. PMC: 4188972. DOI: 10.1523/JNEUROSCI.0989-14.2014. View

5.
Fromer R, Dean Wolf C, Shenhav A . Goal congruency dominates reward value in accounting for behavioral and neural correlates of value-based decision-making. Nat Commun. 2019; 10(1):4926. PMC: 6820735. DOI: 10.1038/s41467-019-12931-x. View