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Completed NON-SBIR/STTR RPGS NIH (US)

Activity-Dependent Tagging of Cerebellar Neurons for Studying Signal Processing and Learning

$1.92M USD

Funder NATIONAL EYE INSTITUTE
Recipient Organization Stanford University
Country United States
Start Date Jan 01, 2021
End Date Dec 31, 2022
Duration 729 days
Number of Grantees 1
Roles Principal Investigator
Data Source NIH (US)
Grant ID 10319181
Grant Description

PROJECT SUMMARY 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.

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Stanford University

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