Impaired representation of temporal statistics in cerebellar degeneration

Abstract

The nervous system represents the statistical structure of the environment to facilitate perception. In time perception, exploiting prior information through Bayesian inference reduces the influence of perceptual noise. However, the neural substrate underlying this computation remains unknown. The cerebellum is a strong candidate whose integrity is essential for motor and perceptual tasks requiring precise timing, and rodent physiological studies indicate that cerebellar plasticity mechanisms can support the encoding of temporal statistics. To examine how the cerebellum is involved in Bayesian timing, we tested patients with cerebellar degeneration and matched controls on duration reproduction tasks with varying prior distributions. Patients showed the signatures of Bayesian inference, but with greater timing variability, stronger regression toward the mean, and slower updating of the prior. We developed a model of the cerebellar microcircuit in which Purkinje cell plasticity over a granule cell temporal basis set provides a shared substrate for the prior and the inference. Simulations of cerebellar degeneration showed deficits consistent with the behavioral changes observed in the patients. These results suggest a critical role for the human cerebellum in Bayesian inference, with the system generating optimally timed behavior across varying contexts and even remaining robust under extensive neuropathology.