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Decision value computation in DLPFC and VMPFC adjusts to the available decision time

Authors

  • Peter Sokol-Hessner,

    1. Division of the Humanities and Social Sciences, California Institute of Technology, 1200 E. California Blvd, Pasadena, CA 91125, USA
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  • Cendri Hutcherson,

    1. Division of the Humanities and Social Sciences, California Institute of Technology, 1200 E. California Blvd, Pasadena, CA 91125, USA
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  • Todd Hare,

    1. Division of the Humanities and Social Sciences, California Institute of Technology, 1200 E. California Blvd, Pasadena, CA 91125, USA
    2. Laboratory for Social and Neural Systems Research, Department of Economics, University of Zurich, Zurich, Switzerland
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  • Antonio Rangel

    1. Division of the Humanities and Social Sciences, California Institute of Technology, 1200 E. California Blvd, Pasadena, CA 91125, USA
    2. Computational and Neural Systems, California Institute of Technology, Pasadena, CA, USA
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Peter Sokol-Hessner, as above.
E-mail: psh@caltech.edu

Abstract

It is increasingly clear that simple decisions are made by computing decision values for the options under consideration, and then comparing these values to make a choice. Computational models of this process suggest that it involves the accumulation of information over time, but little is known about the temporal course of valuation in the brain. To examine this, we manipulated the available decision time and observed the consequences in the brain and behavioral correlates of choice. Participants were scanned with functional magnetic resonance imaging while they chose to eat or not eat basic food items, in two conditions differing in the amount of time provided for choice. After identifying valuation-related regions with unbiased whole-brain general linear models, we analyzed two regions of interest: ventromedial prefrontal cortex (VMPFC) and dorsolateral prefrontal cortex (DLPFC). Finite impulse response models of the upsampled estimated neural activity from those regions allowed us to examine the onset, duration and termination of decision value signals, and to compare across regions. We found evidence for the immediate onset of value computation in both regions, but an extended duration with longer decision time. However, this was not accompanied by behavioral changes in either the accuracy or determinants of choice. Finally, there was modest evidence that DLPFC computation correlated with, but lagged behind, VMPFC computation, suggesting the sharing of information across these regions. These findings have important implications for models of decision value computation and choice.

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