Neural spiking signatures predict behavioral phenotypes of cerebellar movement disorders

Abstract

AbstractThe cerebellum contributes to a diverse array of motor conditions including ataxia, dystonia, and tremor. The neural substrates that encode this diversity are unclear. Here, we tested whether the neural spike activity of cerebellar output neurons predicts the phenotypic presentation of cerebellar pathophysiology. Usingin vivoawake recordings as input data, we trained a supervised classifier model to differentiate the spike parameters between mouse models for ataxia, dystonia, and tremor. The classifier model correctly predicted mouse phenotypes based on single neuron signatures. Spike signatures were shared across etiologically distinct but phenotypically similar disease models. Mimicking these pathophysiological spike signatures with optogenetics induced the predicted motor impairments in otherwise healthy mice. These data show that distinct spike signatures promote the behavioral presentation of cerebellar diseases.