Human perceptual decision making of nonequilibrium fluctuations

To better characterize the statistical processes underlying human decision-making, we performed experiments where human participants visualized fluctuations of physical nonequilibrium stationary states, and we analyzed responses in the context of stochastic thermodynamics. A total of forty five participants viewed hundreds of movies of a particle endowed with drifted Brownian dynamics and were tasked with judging the motion as leftward or rightward in a quick and reliable manner. Overall, the results uncover fundamental performance limits, consistent with recently established thermodynamic trade-offs (uncertainty relations, TURs) involving speed, accuracy, and dissipation; specifically, lower rates of entropy production lead to longer decision times. Moreover, to achieve a given level of observed accuracy, participants require more time than predicted by Wald's optimal sequential probability ratio test, indicating suboptimal integration of available information. In view of such suboptimality, we develop an alternative account equipped with non-Markovian evidence integration with a memory time constant, and find tight fits. Our results suggest that humans adapt their memory relaxation time to the rate of dissipation of the observed phenomenon, favouring memory over momentary evidence for effective decisions in scenarios where stimuli are far from equilibrium. Furthermore, we identify the effects of the environmental stability on decision-making performance and memory by comparing the results of the two sets of experiments: blocked (stationary) versus intermixed (non-stationary) conditions. Our study illustrates that perceptual psychophysics using stimuli rooted in nonequilibrium physical processes provides a robust platform for understanding how the human brain makes decisions on stochastic information inputs.