This Project Summary/Abstract was originally submitted with R01 NS114430 and is included here unchanged to satisfy submission system requirements. PROJECT SUMMARY/ABSTRACT The precision and accuracy of vertebrate movement is mediated, in part, by the cerebellum. Two primary divisions of the cerebellum – the cortex and nuclei – are clearly delineated modules that contribute to behaviorally-relevant computations. Sensorimotor information is first processed by the cortex and is then relayed to the nuclei by Purkinje cells (PCs). The resultant output of the cerebellar nuclei has profound influence on downstream motor control, motivating questions of how nuclear activity is controlled by PCs. In a model behavior, mouse reaching, reach endpoint dysmetria, a hallmark of cerebellar damage, is attributed to the dysfunction of anticipatory braking signals from the cerebellar interposed nucleus that slow the limb near the intended target location. This proposal builds on observations in the previous cycle that the firing rates between Purkinje neurons and their targets in the interposed nucleus are inverse of one another, consistent with a population rate code mediating information transfer. However, in addition to inverse rate coding, we find, as in other species and behaviors, that Purkinje neurons synchronize simple spike firing selectively during behavior. Our proposed studies investigate the sufficiency of PC rate and temporal coding to generate behaviorally relevant adjustments to reach kinematics in mice.The objective of this proposal is to testthe central hypothesis that cerebellar cortical circuits selectively transmit population activity through a synergistic rate and temporal code, imparted by local cortical inhibition, and that this code is refined by learning. We propose to delineate the behavioral significance of PC population coding, how it is generated by cerebellar circuitry, and how motor learning engages the dual nature of this synergistic rate and temporal code. RELEVANCE TO PUBLIC HEALTH: Future therapies targeted at ameliorating cerebellar disease will increasingly leverage understanding of computational mechanisms of the structure, thus identifying those principles, the goal of this proposal, is of central importance.