Social and monetary reward learning engage overlapping neural substrates

Abstract

Learning to make choices that yield rewarding outcomes requires the computation of three distinct signals: stimulus values that are used to guide choices at the time of decision making, experienced utility signals that are used to evaluate the outcomes of those decisions and prediction errors that are used to update the values assigned to stimuli during reward learning. Here we investigated whether monetary and social rewards involve overlapping neural substrates during these computations. Subjects engaged in two probabilistic reward learning tasks that were identical except that rewards were either social (pictures of smiling or angry people) or monetary (gaining or losing money). We found substantial overlap between the two types of rewards for all components of the learning process: a common area of ventromedial prefrontal cortex (vmPFC) correlated with stimulus value at the time of choice and another common area of vmPFC correlated with reward magnitude and common areas in the striatum correlated with prediction errors. Taken together, the findings support the hypothesis that shared anatomical substrates are involved in the computation of both monetary and social rewards.

Fig. 1

Task and behavioral results. (A) Timeline of the monetary and social reward trials. Choice trials paired a neutral slot machine with a valenced slot machine. Trials were identical except for the nature of the outcomes: monetary trials had a gain/loss of +$1, 0$ or −$1, whereas social trials revealed happy, neutral or angry faces accompanied with sound effects of similar emotional valence. The experiment also included no-choice trials (in which a pair of identical slot machines were shown: neutral, negative or positive) to help separate the learning and stimulus value signals. Specific slot machines were randomly assigned to specific reward outcomes at the start of the experiment for each subject, and distinct between monetary and social condition blocks. (B) Distribution of outcomes for each slot machine. First row: negative machine. Second row: positive machine. Bottom row: neutral machine. The same distribution was used in the monetary and social conditions. Actual appearance of the slot machines was randomly paired with a reward outcome distribution and distinct between monetary and social condition blocks. (C) Plot of group subject choices across trials (only the first 30 are shown). (D) Psychometric choice curve for monetary and social conditions. Bars denote standard error measures computed across subjects.

Fig. 2

Basic Neuroimaging results. (Top) Activation in the vmPFC correlated with SV at the time of free choice in both monetary and social conditions. (Middle) Activation in the vStr correlated with PE at the time of outcome in both monetary and social free choice conditions (albeit the conjunction did not survive our omnibus threshold). (Bottom) Activation in the vmPFC correlated with R in both monetary and social free choice conditions. For illustration purposes only, all images are thresholded at P < 0.005 uncorrected with an extent threshold of 15 voxels, except for the conjunction of PE which is P < 0.005 with an extent threshold of five voxels (see Tables 1–3 for details).

Fig. 3

ROI analysis of outcome reward signals in vmPFC during forced choice trials. Average beta plots for activity during reward outcome in forced choice trials. The functional mask of vmPFC is given by the area that exhibits correlation with reward outcomes in social and monetary free choice trials at P < 0.05 SVC. The P-values inside the bars are for t-tests vs zero.