# Cerebellar contributions to reward prediction and decision-making

> **NIH NIH F30** · RBHS-ROBERT WOOD JOHNSON MEDICAL SCHOOL · 2020 · $42,080

## Abstract

Project Summary/Abstract
The cerebellum is a brain structure found in all vertebrates, and it has been studied for decades primarily for its
role in coordinating motor activity. More recently, an abundance of evidence has surfaced linking the
cerebellum to cognitive functions, such as working memory and reward prediction. It is known that the
cerebellum is anatomically connected to the cerebral cortex, and specifically to multiple regions known to be
important for supporting memory and reward-learning functions. However, it remains unknown how the
cerebellum contributes to these cognitive functions, and more generally, what cellular and circuit mechanisms
it employs to process information. To advance our understanding of this region and its role in disease, we will
use a mouse behavioral paradigm that will allow us to investigate the cellular activity of the cerebellum, and to
characterize how it computes information to make these contributions to behavior. We have developed a
behavioral task that is well suited to quantitatively address these questions. We will employ modern
technologies to image and manipulate the activity of cerebellar neurons in awake, behaving mice performing
the task. With two-photon microscopy and genetically encoded calcium indicators, we will visualize the live
activity of hundreds of neurons simultaneously while mice behave. With optogenetics, we will inactivate the
cerebellum during temporally precise phases of the behavior. This will allow us to determine which aspects of
behavior are dependent upon cerebellum. These experiments will enable us to characterize the relationship
between the activity of cerebellar neuronal networks and behavior. By studying cerebellar activity at the level of
neural circuits during behavior, we will characterize how the cerebellum contributes to normal and abnormal
cognitive function. With improved characterization of the circuits that are commonly dysfunctional in prevalent
neuropsychiatric diseases like autism and schizophrenia, we will come closer to understanding the underlying
causes of these disorders and of normal brain function.

## Key facts

- **NIH application ID:** 10007900
- **Project number:** 5F30MH115577-04
- **Recipient organization:** RBHS-ROBERT WOOD JOHNSON MEDICAL SCHOOL
- **Principal Investigator:** Benson Deverett
- **Activity code:** F30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $42,080
- **Award type:** 5
- **Project period:** 2017-09-15 → 2021-05-14

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10007900

## Citation

> US National Institutes of Health, RePORTER application 10007900, Cerebellar contributions to reward prediction and decision-making (5F30MH115577-04). Retrieved via AI Analytics 2026-06-01 from https://api.ai-analytics.org/grant/nih/10007900. Licensed CC0.

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