4.7 Article

Neural Mechanisms Underlying Contextual Dependency of Subjective Values: Converging Evidence from Monkeys and Humans

Journal

JOURNAL OF NEUROSCIENCE
Volume 35, Issue 5, Pages 2308-2320

Publisher

SOC NEUROSCIENCE
DOI: 10.1523/JNEUROSCI.1878-14.2015

Keywords

decision making; electrophysiology; fMRI; neuroeconomics; reward; ventromedial prefrontal cortex

Categories

Funding

  1. European Research Council
  2. National Institutes of Health Intra-Mural Research Program
  3. French Direction Generale de l'Armement and Investissement d'avenir [ANR-10-IAIHU-06]

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A major challenge for decision theory is to account for the instability of expressed preferences across time and context. Such variability could arise from specific properties of the brain system used to assign subjective values. Growing evidence has identified the ventromedial prefrontal cortex (VMPFC) as a key node of the human brain valuation system. Here, we first replicate this observation with an fMRI study in humans showing that subjective values of painting pictures, as expressed in explicit pleasantness ratings, are specifically encoded in the VMPFC. We then establish a bridge with monkey electrophysiology, by comparing single-unit activity evoked by visual cues between theVMPFCand the orbitofrontal cortex. At the neural population level, expected reward magnitude was only encoded in the VMPFC, which also reflected subjective cue values, as expressed in Pavlovian appetitive responses. In addition, we demonstrate in both species that the additive effect of prestimulus activity on evoked activity has a significant impact on subjective values. In monkeys, the factor dominating prestimulus VMPFC activity was trial number, which likely indexed variations in internal dispositions related to fatigue or satiety. In humans, prestimulus VMPF Cactivity was externally manipulated through changes in the musical context, which induced a systematic bias in subjective values. Thus, the apparent stochasticity of preferences might relate to the VMPFC automatically aggregating the values of contextual features, which would bias subsequent valuation because of temporal autocorrelation in neural activity.

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