Humans are often inconsistent (irrational) when choosing among simple bundles of goods, even without any particular changes to framing or context. However, the neural computations that give rise to such inconsistencies are still unknown. Similar to sensory perception and motor output, we propose that a substantial component of inconsistent behavior is due to variability in the neural computation of value. Here, we develop a novel index that measures the severity of inconsistency of each choice, enabling us to directly trace its neural correlates. We find that the BOLD signal in the vmPFC, ACC, and PCC is correlated with the severity of inconsistency on each trial and with the subjective value of the chosen alternative. This suggests that deviations from rational choice arise in the regions responsible for value computation. We offer a computational model of how variability in value computation is a source of inconsistent choices.

Ample evidence shows that humans violate fundamental economic axioms. Yet, the neural mechanism underlying inconsistent (or irrational) choices remains obscure. Here, we aim to show that inconsistent choices could rise either due to value miscalculations or due to motor errors during task execution. We report the results from two independent behavioral and neuroimaging studies. Subjects completed a risky-choice task to test their inconsistency levels, followed by two novel tasks, designed to solely examine motor output. We recorded mouse trajectories during task execution and designed 34 features to analyze choice dynamics. We show that choice dynamics predict inconsistency levels, even when motor output was absent any valuation elements. In the neuroimaging study, we show that inconsistency is tied to noisy value computations in reward circuits, but at the same time, is also related to noisy neural motor dynamics. These findings suggest that (at least) two neural sources of noise contribute to inconsistent choice behavior.