Neural responses to advantageous and disadvantageous inequity

Abstract

In this paper we study neural responses to inequitable distributions of rewards despite equal performance. We specifically focus on differences between advantageous inequity (AI) and disadvantageous inequity (DI). AI and DI were realized in a hyperscanning functional magnetic resonance imaging (fMRI) experiment with pairs of subjects simultaneously performing a task in adjacent scanners and observing both subjects' rewards. Results showed (1) hypoactivation of the ventral striatum (VS) under DI but not under AI; (2) inequity induced activation of the right dorsolateral prefrontal cortex (DLPFC) that was stronger under DI than under AI; (3) correlations between subjective evaluations of AI evaluation and bilateral ventrolateral prefrontal and left insular activity. Our study provides neurophysiological evidence for different cognitive processes that occur when exposed to DI and AI, respectively. One possible interpretation is that any form of inequity represents a norm violation, but that important differences between AI and DI emerge from an asymmetric involvement of status concerns.

Keywords: equity norm; functional magnetic resonance imaging (fMRI); social preferences; ventral striatum.

Figure 1

Single-trial settings. Subjects saw a number of blue dots for 1500 ms (screen 1). Immediately afterwards, a number was presented and subjects had to decide by pressing a button whether the number of dots on the first screen was less than or greater than this number within a time limit of 1500 ms (screen 2). After a response feedback (250 ms, screen 3) and a short delay (blank screen 4), a feedback screen informed subjects about their own and the other subject's performance (correct or incorrect) together with the respective monetary rewards (screen 5). Here, three alternative outcomes representing the main conditions for this study are depicted.

Figure 2

ROI Masks. In red: Voxels within the striatum which show a reward-related signal (derived from the contrast C2, C3 > C1, C4, and C5) on a P_FWE < 0.05 (per voxel), whole brain corrected. In blue: anatomically defined NAcc mask (according to Harvard-Oxford brain atlas).

Figure 3

Mean pleasantness ratings for the conditions DI (own income/other's income: 60/120), E (60/60), and AI (60/30). Error bars indicate the standard error of the mean (SEM). ^*p < 0.05, ^***p < 0.001 (dependent samples t-tests).

Figure 4

Results for the ventral striatum. Left: Brain images showing significantly (P < 0.005 for demonstration purposes) higher activation for E than DI (peakvoxel MNI-coordinates: X = −6, Y = 14, Z = −5), and for AI than for DI (X = −12, Y = 11, Z = −5), within the functionally defined ROI. Right: The barplot shows mean parameter estimates for the different conditions averaged across all voxels of the functionally defined ROI. The left side demonstrates the strong responsiveness of the area to rewards per se (which was the selection criterion for the ROI, implying circularity of this result). The right side shows a significant main effect of relative payoff on activation in this area [within-subject ANOVA: (F_{(2, 59)} = 8.26, P < 0.001)] with stronger acvtivation in the equity (t₆₃ = 2.76, P = 0.007) and advantageous inequity (t = 3.56, P < 0.001) condition than for the disadvantageous inequity condition. Note that these contrasts are independent of the ROI defining contrasts. Error bars indicate standard error of means and are not informative with regard to (within-subjects) statistical inference.

Figure 5

Results for the anatomically defined ROI: Mean parameter estimates for the different conditions averaged across all voxels of the ROI (cf. Figure 3). The left side demonstrates the strong responsiveness of the area to rewards per se. The right side shows a significant main effect of relative payoff on activation in this area [within-subject ANOVA: (F_{(2, 59)} = 6.556, P = 0.008)] with stronger activation in the E (t₆₃ = 2.32, P = 0.023) and advantageous inequity (t = 2.92, P < 0.001) condition than for the disadvantageous inequity condition. Error bars indicate standard error of means and are not informative with regard to (within-subjects) statistical inference.

Figure 6

Association of BOLD responses to ratings in the VS (averaged across all voxels of the functionally defined ROI) and subjective pleasentness ratings demonstrate a significant positive association between pleasantness and signal for AI evaluation (r = 0.29, P = 0.01, one-sided) and a non-significant trend for DI evaluation (R = 0.18, P = 0.08, one-sided).

Figure 7

Whole-brain analysis of the contrast DI > E. Left: Significant activation cluster (cluster corrected P_FWE < 0.005, inclusion threshold P < 0.001 unc.) in the rDLPFC (Peak voxel MNI coordinates X = 48, Y = 29, Z = 37). The majority of the voxels lie in Brodman Area 9. Right: The bar plot depicts effects of the different conditions at the peak voxel (plus surrounding 5 mm). Note that this diagram only serves demonstration reasons. Error bars indicate standard error of means and are not informative with regard to (within-subjects) statistical inference.

Figure 8

Whole-brain correlational analysis of the contrast E-AI with the respective difference in the pleasantness rating. Significant clusters (cluster corrected P_FWE < 0.005, inclusion threshold P < 0.001 unc.) showing this relation lie bilaterally in the VLPFC (Peak voxel MNI coordinates: X = 45, Y = 32, Z = 1, and X = −57, Y = 35, Z = 1) and in the left insula (X = −33, Y = 2, Z = −2). Right: The scatterplot depicts the relation between contrast and ratings for the peak voxels averaged across both sides of the VLMPFC clusters, and serves demonstration reasons only.