Motion direction biases around the clock: Learned and in-built direction priors pull perception and pursuit apart

Visual motion perception and pursuit eye movements rely on integrating uncertain sensory input with prior knowledge. Previous work has extensively investigated motion perception biases from experience-related or innate priors. In parallel, since Eileen Kowler's pioneering work, anticipatory smooth eye movements have been studied as an indicator of cognitive expectations. However, whether perception and eye movements rely on the same priors and computational operations (e.g., Bayesian reliability-based integration) remains only partly understood. Additionally, the role of natural directional biases in two-dimensional space (e.g., cardinal preferences) and their interaction with immediate motion expectations have not been explored. To address these questions, we measured smooth pursuit and direction estimations in human volunteers tracking random dot kinematograms with a proportion of coherent dots (5%, 15%, or 40%) moving in one of 16 directions between -180° and +180° across three sessions: one with uniformly distributed directions and two including a specific directional bias. Under high uncertainty, inaccurate direction estimations systematically avoided the most frequent direction in biased sessions, contrary to the Bayesian attraction-to-prior predictions, and generally favored cardinal directions. In contrast, eye movements agreed with the attraction-to-prior effect: Anticipatory pursuit roughly aligned with expected directions, and early pursuit acceleration was enhanced when stimulus direction matched expectation. These findings highlight a dissociation between perception and pursuit in directional biases induced across time scales in two-dimensional space. This suggests that the two systems either rely on partly different internal models or use shared priors differently, pointing to a layered, task-dependent organization of motion inference in the brain.