TY - JOUR
T1 - Individual differences in (dis)honesty are represented in the brain's functional connectivity at rest
AU - Speer, Sebastian P H
AU - Smidts, Ale
AU - Boksem, Maarten A S
N1 - Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.
PY - 2022
Y1 - 2022
N2 - Measurement of the determinants of socially undesirable behaviors, such as dishonesty, are complicated and obscured by social desirability biases. To circumvent these biases, we used connectome-based predictive modeling (CPM) on resting state functional connectivity patterns in combination with a novel task which inconspicuously measures voluntary cheating to gain access to the neurocognitive determinants of (dis)honesty. Specifically, we investigated whether task-independent neural patterns within the brain at rest could be used to predict a propensity for (dis)honest behavior. Our analyses revealed that functional connectivity, especially between brain networks linked to self-referential thinking (vmPFC, temporal poles, and PCC) and reward processing (caudate nucleus), reliably correlates, in an independent sample, with participants' propensity to cheat. Participants who cheated the most also scored highest on several self-report measures of impulsivity which underscores the generalizability of our results. Notably, when comparing neural and self-report measures, the neural measures were found to be more important in predicting cheating propensity.
AB - Measurement of the determinants of socially undesirable behaviors, such as dishonesty, are complicated and obscured by social desirability biases. To circumvent these biases, we used connectome-based predictive modeling (CPM) on resting state functional connectivity patterns in combination with a novel task which inconspicuously measures voluntary cheating to gain access to the neurocognitive determinants of (dis)honesty. Specifically, we investigated whether task-independent neural patterns within the brain at rest could be used to predict a propensity for (dis)honest behavior. Our analyses revealed that functional connectivity, especially between brain networks linked to self-referential thinking (vmPFC, temporal poles, and PCC) and reward processing (caudate nucleus), reliably correlates, in an independent sample, with participants' propensity to cheat. Participants who cheated the most also scored highest on several self-report measures of impulsivity which underscores the generalizability of our results. Notably, when comparing neural and self-report measures, the neural measures were found to be more important in predicting cheating propensity.
U2 - 10.1016/j.neuroimage.2021.118761
DO - 10.1016/j.neuroimage.2021.118761
M3 - Article
C2 - 34861396
SN - 1053-8119
VL - 246
SP - 118761
JO - NeuroImage
JF - NeuroImage
ER -