No Discrete Start/Stop Signals in the Dorsal Striatum of Mice Performing a Learned Action

Abstract

A popular hypothesis is that the dorsal striatum generates discrete "traffic light" signals that initiate, maintain, and terminate the execution of learned actions. Alternatively, the striatum may continuously monitor the dynamics of movements associated with action execution by processing inputs from somatosensory and motor cortices. Here, we recorded the activity of striatal neurons in mice performing a run-and-stop task and characterized the diversity of firing rate modulations relative to run performance (tuning curves) across neurons. We found that the tuning curves could not be statistically clustered in discrete functional groups (start or stop neurons). Rather, their shape varied continuously according to the movement dynamics of the task. Moreover, striatal spiking activity correlated with running speed on a run-by-run basis and was modulated by task-related non-locomotor movements, such as licking. We hypothesize that such moment-to-moment movement monitoring by the dorsal striatum contributes to the learning of adaptive actions and/or updating their kinematics.

Keywords: Bayesian decoding; action; basal ganglia; behavior; caudate; locomotion; movement; neuronal sequence; population activity; putamen.