# Neuroanatomic and Functional Characterization of Cerebellar Circuits Mediating Ingestive Behaviors

> **NIH NIH R01** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2024 · $588,277

## Abstract

Project Summary/Abstract
Understanding the interconnected web of brain circuits that regulate body weight (fat) is vital for the prevention
and treatment of obesity. The goal of this proposal is to establish a novel role for the cerebellum in feeding
behaviors related to obesity. The vast computational power of the cerebellum (>1/2 of all neurons in the human
brain are cerebellar granule cells) has traditionally been considered in relation to movement. However, mounting
evidence suggests that cerebellar machinery for learning and predictive control operates across a much wider
domain: ranging from autonomic functions to cognitive and motivated behaviors. Guided by our recent finding of
a specific region of the mouse cerebellum that potently drives ingestive behavior, the proposed experiments
leverage state-of-the-art methods for mapping, monitoring, and manipulating neural circuits in mice to elucidate
cerebellar roles in feeding behavior. The proposed studies will lay the groundwork for imputing a vital role of the
cerebellum in optimizing feeding behaviors in the context of extant physiological and environmental conditions.

## Key facts

- **NIH application ID:** 10854869
- **Project number:** 5R01DK131086-03
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** RUDOLPH L LEIBEL
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $588,277
- **Award type:** 5
- **Project period:** 2022-07-20 → 2027-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10854869

## Citation

> US National Institutes of Health, RePORTER application 10854869, Neuroanatomic and Functional Characterization of Cerebellar Circuits Mediating Ingestive Behaviors (5R01DK131086-03). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10854869. Licensed CC0.

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