A dynamic code for economic object valuation in prefrontal cortex neurons.

Ken-Ichiro Tsutsui,Wolfram Schultz,Fabian Grabenhorst,Shunsuke Kobayashi

doi:10.1038/ncomms12554

Ken-Ichiro Tsutsui, Wolfram Schultz + Show 2 more

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https://doi.org/10.1038/ncomms12554

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Abstract

Neuronal reward valuations provide the physiological basis for economic behaviour. Yet, how such valuations are converted to economic decisions remains unclear. Here we show that the dorsolateral prefrontal cortex (DLPFC) implements a flexible value code based on object-specific valuations by single neurons. As monkeys perform a reward-based foraging task, individual DLPFC neurons signal the value of specific choice objects derived from recent experience. These neuronal object values satisfy principles of competitive choice mechanisms, track performance fluctuations and follow predictions of a classical behavioural model (Herrnstein’s matching law). Individual neurons dynamically encode both, the updating of object values from recently experienced rewards, and their subsequent conversion to object choices during decision-making. Decoding from unselected populations enables a read-out of motivational and decision variables not emphasized by individual neurons. These findings suggest a dynamic single-neuron and population value code in DLPFC that advances from reward experiences to economic object values and future choices.

Highlights

We hypothesized that individual dorsolateral prefrontal cortex (DLPFC) neurons encode the construction of values from experience, their formatting into object-specific decision variables, and their conversion to object choices
We show that individual DLPFC neurons dynamically encode the value of specific choice objects as a decision variable
We found that individual DLPFC neurons encoded internal value estimates derived from the fluctuating reward probabilities of specific choice objects

Summary

Introduction

We hypothesized that individual DLPFC neurons encode the construction of values from experience, their formatting into object-specific decision variables, and their conversion to object choices. We show that individual DLPFC neurons dynamically encode the value of specific choice objects as a decision variable. Individual neurons signal both the construction of object values from recently experienced rewards and their subsequent conversion to object choices. Population decoding demonstrates a dynamic readout of additional value-derived variables not encoded by individual neuron, which meet the motivational and decision requirements of different task stages. This dynamic object value code— characterized by single-neuron convergence of valuation, learning, and decision signals and flexible population readout—may support DLPFC’s signature role in adaptive behavior

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