Figure 3.

Computational modeling. (a) Green shaded region captures willingness to sacrifice own payoffs to send the true message, i.e., bias toward honesty, where weight on self-interest in the Message condition (α_M) is reduced relative to the Choice condition (α_C). Conversely, red shaded region captures willingness to sacrifice own payoffs to send the false message, i.e., bias toward dishonesty, where α_M is greater than α_C. All cohorts placed similar weights on one’s own payoff in the Choice condition (DLPFC: . 82 ± .05, OFC: . 79 ± .07 and healthy comparison: . 73 ± .05). In the Message condition, OFC and healthy participants showed a significant reduction in weight on own payoff, whereas DLPFC participants did not differ significantly between the two conditions (DLPFC: . 75 ± .09; OFC: .43 ± .06; and healthy comparison:. 29 ± .04). Solid points represent parameter estimates and smaller points represent bootstrap pseudo-sample estimates. Dashed ellipses correspond to bootstrapped standard errors. (b) Taking paired-wise differences in pseudo-sample estimates of α_M and α_C, OFC and healthy participants showed significantly lower weight on own payoff in the Message condition as compared to the Choice condition (p < .01, two-tailed), whereas the DLPFC cohort did not exhibit a significant difference (p > .05, two-tailed; all error bars indicate bootstrap standard errors).