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Published February 5, 2014 | Supplemental Material + Accepted Version
Journal Article Open

Neural Computations Underlying Arbitration between Model-Based and Model-free Learning

Abstract

There is accumulating neural evidence to support the existence of two distinct systems for guiding action selection, a deliberative "model-based" and a reflexive "model-free" system. However, little is known about how the brain determines which of these systems controls behavior at one moment in time. We provide evidence for an arbitration mechanism that allocates the degree of control over behavior by model-based and model-free systems as a function of the reliability of their respective predictions. We show that the inferior lateral prefrontal and frontopolar cortex encode both reliability signals and the output of a comparison between those signals, implicating these regions in the arbitration process. Moreover, connectivity between these regions and model-free valuation areas is negatively modulated by the degree of model-based control in the arbitrator, suggesting that arbitration may work through modulation of the model-free valuation system when the arbitrator deems that the model-based system should drive behavior.

Additional Information

© 2014 Elsevier Inc. Accepted: November 25, 2013; Published: February 5, 2014. Supplemental Information includes five figures, five tables, and Supplemental Experimental Procedures and can be found with this article online at http://dx.doi.org/10.1016/j.neuron.2013.11.028. We thank Mimi Liljeholm and Peter Bossaerts for suggestions and insightful comments and Ralph Lee for his assistance. This work was funded by NIH grant DA033077-01 (supported by OppNet, NIH's Basic Behavioral and Social Science Opportunity Network) to J.P.O.D., by funds from the Gordon and Betty foundation to J.P.O.D., by grants from JST-CREST to S.S., and by the Caltech-Tamagawa gCOE to S.S. and J.P.O.D.

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Accepted Version - nihms-560387.pdf

Supplemental Material - mmc1.pdf

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