Mapping cerebellar granule cell function with novel genetic and optical tools

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Project Summary/Abstract Recent evidence from multiple laboratories in both human and animal models supports a role for the granule cell (GrC) pathway of the cerebellum in representing a wide range of sensory, motor, and internal information. Classical theories of cerebellar function proposed that activity in a small number of GrCs (<1%) encodes a particular sensorimotor context. However, recent population level calcium imaging studies of GrC somata indicate that populations of GrCs encode sensory and motor events, and complex properties such as reward and motor preparation. However, these studies lacked the temporal resolution to identify specific relationships between those events and GrC firing. Both study designs also precluded direct determination of what input pathways drove the observed patterns of GrC activity. A comprehensive understanding of the input-output transform performed by GrCs will require the ability to precisely perturb anatomically specific descending inputs while densely recording the resultant patterns of activity with high spatiotemporal precision. To approach this set of methodological gaps, I propose to (1) holistically develop a spike-counting method for genetically encoded indicators (GECIs) by adjusting current sensor properties and creating a biophysical in vivo model of the calcium sensor GCaMP, (2) optogenetically perturb neocortex to map its functional inputs to GrCs while optically accessing the entire cerebellar surface, and (3) use a rodent behavioral task to disambiguate sensory, motor and internal-state contributions to granule cell activity patterns. Completion of these aims will allow a direct test of whether GrCs indeed make a sparse representation of their input signals. I also aim to provide the most comprehensive analysis to date on the makeup of the inputs that drive GrC activity.