Testing the reinforcement learning hypothesis of social conformity

Abstract

Our preferences are influenced by the opinions of others. The past human neuroimaging studies on social conformity have identified a network of brain regions related to social conformity that includes the posterior medial frontal cortex (pMFC), anterior insula, and striatum. Since these brain regions are also known to play important roles in reinforcement learning (i.e., processing prediction error), it was previously hypothesized that social conformity and reinforcement learning have a common neural mechanism. However, although this view is currently widely accepted, these two processes have never been directly compared; therefore, the extent to which they shared a common neural mechanism had remained unclear. This study aimed to formally test the hypothesis. The same group of participants (n = 25) performed social conformity and reinforcement learning tasks inside a functional magnetic resonance imaging (fMRI) scanner. Univariate fMRI data analyses revealed activation overlaps in the pMFC and bilateral insula between social conflict and unsigned prediction error and in the striatum between social conflict and signed prediction error. We further conducted multivoxel pattern analysis (MVPA) for more direct evidence of a shared neural mechanism. MVPA did not reveal any evidence to support the hypothesis in any of these regions but found that activation patterns between social conflict and prediction error in these regions were largely distinct. Taken together, the present study provides no clear evidence of a common neural mechanism between social conformity and reinforcement learning.

Keywords: MVPA; fMRI; prediction error; reinforcement learning; social conformity.

FIGURE 1

Experimental tasks. (a) Social conformity task. Participants were shown images of female faces and a 10‐point scale and asked to rate the attractiveness of each face. After the participants submitted their ratings, they were shown the ratings of each face by other people (in blue frame) for 2 s. (b) Reinforcement learning task (probabilistic reward learning task). Participants were presented with two slot machines and asked to pick 1 of them. After the participants made their decisions, they were presented with a win or loss outcome

FIGURE 2

Schematic illustrations of two types of MVPA. (a) Correlation‐based MVPA tests if the two patterns are significantly similar. (b) Classifier‐based MVPA tests if the two patterns are significantly distinct

FIGURE 3

fMRI results from univariate analyses. (a) pMFC and insula regions positively related to social conflict (i.e., absolute difference between participant and group ratings). (b) Striatum regions negatively related to social conflict. (c) pMFC and insula regions positively related to unsigned prediction error. (d) Striatum regions positively related to signed prediction error. (e) Activation overlaps between social conflict (panel a) vs. unsigned prediction error (panel c) related regions. (f) Activation overlaps between social conflict (panel b) vs. unsigned prediction error (panel d) related regions

FIGURE 4

Searchlight MVPA. (a) Functional ROIs used in the searchlight MVPAs. Yellow color denotes regions sensitive to social conflict (positively related) and unsigned prediction error. Cyan color denotes regions sensitive to social conflict (negatively related) and signed prediction error. (b) Searchlight MVPA results (classifier‐based MVPA). Each panel depicts areas that showed significantly distinct activation patterns between social conflict and signed/unsigned prediction error