Figure 3.

A. The bilateral entorhinal cortex (EC) and ventromedial prefrontal cortex (vmPFC/mOFC), p_TFCE<0.05 corrected within a small volume ROI encode the Euclidean distance from the hub (H2) to F1 in the 2-D social space (E_H2F1). Whole-brain parametric analyses showing neural correlates of each of the distance metrics that could theoretically drive inferences between pairs at the time of decisions (F2 presentation). D: 1-D rank distance in the task-relevant dimension (D_H2F1 and D_F1F2); L: the shortest link distance between F1 and F2 (L equals to D_H2F1+1); I: the 1-D rank distance in the task-irrelevant dimension (I_H2F1 and I_F1F2); A: the cosine vector angle (A_H2F1 and A_F1F2). For visualization purposes, the whole-brain maps are thresholded at p<0.005 uncorrected. B. The results of Bayesian model selection (BMS). The exceedance probabilities revealed that the Euclidean distance from the hub (E_H2F1) best accounted for variance in both EC and vmPFC/mOFC activity compared to the other distance measures, providing evidence that these regions compute or reflect a Euclidean distance metric to a retrieved hub (H2) in abstract space in order to infer the relationship between F1 and F2. C. Conjunction analysis shown in purple revealed that both D_H2F1 and I_H2F1 are reflected in the vmPFC/mOFC and the EC bilaterally. D. The effect of D_H2F1 does not differ from I_H2F1 in the EC or vmPFC/mOFC, even at a lenient threshold (p>0.1), suggesting that these areas assign equal or similar weights to D_H2F1 and I_H2F1, consistent with activity reflecting E_H2F1, during decision-making.