Supplementary Figure 7: Increased vmPFC response for OCU-modified variables is consistent across multiple additional variables and greatest for U_{with OCU} chosen gamble - U_{with OCU} unchosen gamble (pink).

It is possible that other variables than ‘U_{with OCU} chosen gamble – U_{with OCU} unchosen gamble (Fig. 3ai)’ show an enhanced vmPFC signal when modified by OCU, as U_{with OCU} is posited to be a closer approximation of participants’ subjective value (on Info trials) than is U_solo. To address this possibility, we ran several additional analyses with and without OCU modifying several different variables (U_safe, U_risky, U_safe – U_risky, U_chosen, and U_total) to examine whether the OCU-modified utility signals show stronger neural correlates than the unmodified variables. We focused on vmPFC activity in the INFO trials because OCU modification only exists on these trials (for Solo trials, OCU = 0 as there is no information from others). Using these additional regressors, we observed that in every case, vmPFC activity for utility differences between the chosen and unchosen gambles (pink, U_{with OCU} chosen gamble – U_{with OCU} unchosen gamble) was greater than neural responses associated with each of the other additional regressors (gray bars; using the Fig. 3ai cluster as the ROI; paired t-tests: U_risky, t(55) = –2.87, P = 0.0059; U_safe, t(55) = –3.36, P = 0.0014 ; U_risky-U_safe, t(55) = –2.79, P = 0.0072; U_total, t(55) = –2.98, P = 0.0043; U_chosen, t(55) = –2.08, P = 0.042). Equally important, for 4 of these 5 additional regressors, the OCU-modified variable showed at least a trend toward better performance than the un-modified variable (gray vs black bars; paired t-tests: U_risky, t(55) = –2.49, P = 0.016; U_safe, t(55) = 1.28, P = 0.21; U_risky–U_safe, t(55) = –2.03, P = 0.047; U_total (U_safe+U_risky), t(55) = –2.22, P = 0.031; U_chosen, t(55) = –1.32, P = 0.19). The better performance for the OCU-modified variables is notable in its consistency across variables, and provides additional support for our hypothesis that others choices confer subjective value to those options. That is, under this hypothesis, we expected to see stronger vmPFC encoding of OCU-modified variables, given that U_{with OCU} is posited to be a closer approximation of participants’ subjective value (on Info trials) than is U_solo alone. In addition, to test the differences between beta for U_{chosen OCU} – U_{unchosen OCU} and each of the listed other OCU-modified variables, we ran a series of paired t-tests. The vmPFC beta obtained from U_{chosen OCU} – U_{unchosen OCU} was larger than each of the other 5 OCU-modified variables at least at the trend level (each variable tested vs beta for U_{chosen OCU} – U_{unchosen OCU}, paired t-tests: U_{risky OCU}, t(55) = –1.68, P = 0.099; U_{safe OCU}, t(55) = –3.88, P = 0.00028; U_{risky OCU} – U_{safe OCU}, t(55) = –1.79, P = 0.079; U_{total OCU}, t(55) = –2.22, P = 0.030; U_{chosen OCU}, t(55) = –1.52, P = 0.13). We note that beta for U_{chosen OCU} – U_{unchosen OCU} is not necessarily expected to be significantly better than each of the other OCU-modified variables. Specifically, other OCU-modified variables (including and beyond those tested here), may contribute with varying weight to participants’ choices. We focused here on beta for U_{chosen OCU} – U_{unchosen OCU} as the broadest OCU-modified variable likely to be encoded. It is likely (and suggested by these analyses) that individual differences exist for the types of information to which others choices confer value and that are compiled into a participant’s decisions. Unmodified variables are shown in gray, OCU-modified variable are shown in black. Error bars show s.e.m.; * P < 0.05, n.s., not significant.