Attractor dynamics of working memory explain a concurrent evolution of stimulus-specific and decision-consistent biases in visual estimation

Abstract

Sensory evidence tends to be fleeting, often unavailable when we categorize or estimate world features. To overcome this, our brains sustain sensory information in working memory. Although keeping that information accurate while acting on it is vital, humans display two canonical biases: estimates are biased toward a few stimuli ("stimulus-specific bias") and prior decisions ("decision-consistent bias"). Integrative--especially neural mechanistic--accounts of these biases remain scarce. Here, we identify drift dynamics toward discrete attractors as a common source of both biases in orientation estimation, with decisions further steering memory states. Behavior and neuroimaging data reveal how these biases co-evolve through the decision-steered attractor dynamics. Task-optimized recurrent neural networks suggest neural mechanisms that enable categorical decisions to emerge from working memory for continuous stimuli while updating its trajectory, warping decision-consistent biases under stimulus-specific drift.