Control of the strength of visual-motor transmission as the mechanism of rapid adaptation of priors for Bayesian inference in smooth pursuit eye movements

Bayesian inference provides a cogent account of how the brain combines sensory information with "priors" based on past experience to guide many behaviors, including smooth pursuit eye movements. We now demonstrate very rapid adaptation of the pursuit system's priors for target direction and speed. We go on to leverage that adaptation to outline possible neural mechanisms that could cause pursuit to show features consistent with Bayesian inference. Adaptation of the prior causes changes in the eye speed and direction at the initiation of pursuit. The adaptation appears after a single trial, and accumulates over repeated exposure to a given history of target speeds and directions. The influence of the priors depends on the reliability of visual motion signals: priors are more effective against the visual motion signals provided by low-contrast versus high-contrast targets. Adaptation of the direction prior generalizes to eye speed, and vice versa, suggesting that both priors could be controlled by a single neural mechanism. We conclude that the pursuit system can learn the statistics of visual motion rapidly and use those statistics to guide future behavior. Further, a model that adjusts the gain of visual-motor transmission predicts the effects of recent experience on pursuit direction and speed, as well as the specifics of the generalization between the priors for speed and direction. We suggest that Bayesian inference in pursuit behavior is implemented by distinctly non-Bayesian internal mechanisms that use the smooth eye movement region of the frontal eye fields to control of the gain of visual-motor transmission.

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