Thermodynamic tradeoffs constrain decision-making of nonequilibria in the human brain

Perceptual decision-making frequently requires making rapid, reliable choices upon encountering noisy sensory inputs. To better define the statistical processes underlying perceptual decision-making, we characterize the choices of human participants visualizing a system of nonequilibrium stationary physical dynamics and compare such choices to the performance of an optimal agent computing Wald’s sequential probability ratio test (SPRT). Participants viewed movies of a drifted Brownian particle and had to judge the motion as leftward or rightward. Overall, the results uncovered fundamental performance limits consistent with recently established thermodynamic tradeoffs involving speed, accuracy, and dissipation. Specifically, decision times are sensitive to entropy production rates. To achieve a given level of accuracy, participants require more time than that predicted by the SPRT, indicating suboptimal integration of available information. Given such suboptimality, we develop an alternative account based on evidence integration with a memory time constant. Setting the time constant proportionate to the deviation from equilibrium in the stimuli significantly improves trial-by-trial predictions of decision metrics with respect to SPRT. This study shows that perceptual psychophysics using stimuli rooted in nonequilibrium physical processes provides a robust platform for understanding how the brain decides on stochastic information.