Conference on Cognitive Computational Neuroscience

Economic theories usually assume that humans maximize utility in their choices. However, studies have shown for decades that humans make inconsistent choices, leading to suboptimal behavior. Previous studies showed that activations in value and motor networks are associated with inconsistent choices at the moment of choice. Here we investigate whether neural predispositions, measured before a choice task, can predict choice inconsistency. Using functional connectivity (FC) measures from resting-state functional magnetic resonance imaging (rs-fMRI) we aimed to predict subjects’ inconsistency levels in a later-performed choice task. We hypothesized that connectivity between value and motor regions would predict inconsistency. Forty subjects completed a rs-fMRI scan before performing a risky-choice task. We compared models that were trained on FC that included only hypothesized value and motor regions with whole-brain models. We found that both models significantly predicted inconsistency levels. Moreover, even the whole-brain models relied mostly on FC between value and motor areas. For external validation, we used a neural network pre-trained on 40,000 subjects and fine-tuned it, again showing significant predictions of inconsistency. In conclusion, the tendency for choice inconsistency is predicted by neural predispositions, and the synchrony between the motor and value networks plays a crucial role in this tendency.