The goal of the proposed research is to implement state-of-the-art techniques for recording and manipulating neurons based on their activity in the cerebellum, to dissect the computations performed by the cerebellum to control eye movements. Vision is an active sense, and the accurate control of eye movements plays an essential role in vision. The cerebellum plays a key role in the control of eye movements, and in the refinement of eye movement accuracy and precision through oculomotor learning. It is known that the part of the cerebellum controlling eye movements receives visual and vestibular sensory information as well as copies of the eye movement commands, and presumably uses these sensory and motor signals to guide oculomotor performance and its modification by learning. However, a number of technical challenges have limited our ability to study how different sensory and motor signals are integrated in the cerebellum, and how the different signaling pathways are each modified during learning to improve oculomotor performance. Two newly developed tools, CaMPARI and Cal-Light, hold great promise to overcome some of the technical challenges that have limited studies of cerebellar computation. These tools offer advanced precision in the ability to record and manipulate neurons based on their activity during specific task conditions. We will (1) evaluate the efficacy of CAMPARI and Cal-light for selectively targeting (?tagging?), subpopulations of cerebellar neurons in a task- and activity-dependent manner, and (2) use these tools to dissect the computations implemented by the cerebellum during oculomotor performance and oculomotor skill learning. The technical outcome of the proposed work will be a new set of experimental approaches for studying the cerebellum, as well as new experimental strategies for studying computation and learning in other neural circuits. The scientific outcome will be new insights about the computations performed by the cerebellum on its sensory (visual and vestibular) and motor (efference copy) inputs. Advances in understanding how the cerebellum supports accurate eye movements will provide conceptual underpinning for developing more rational interventions for oculomotor disorders, and, more generally for the wide array of disorders associated with cerebellar dysfunction.
This project will apply newly developed methods for molecularly tagging neurons based on their activity to functionally dissect the cerebellar circuitry. The proposed work will analyze the overlap of neural ensembles carrying different kinds of information to control eye movements, and how the pathways carrying different kinds of information each change during motor skill learning. The results should establish a new approach for analyzing the computations performed by the cerebellum to support behavior, and how those computations are adaptively modified by learning.
