# The function of dopamine and striatal neurons in guiding behavior in uncertain environments

> **NIH NIH U19** · HARVARD MEDICAL SCHOOL · 2020 · $777,821

## Abstract

Project abstract
Animals must acquire and integrate information over time in order to make decisions. In addition, as the
environment changes, animals must use new information to update previous models of the world and revise
their decision making process. We observe such decision making processes in mice by challenging them to
use changing and probabilistic environmental information to choose a motor action to achieve water rewards.
These tasks engage the striatum and evoke dynamic dopamine signaling which is thought to be crucial to the
decision making process. Here we will use modern methods of analysis of motor action with simultaneous
observation of bilateral activity in the dorsal and ventral striatum to understand how features of behavior, the
environment, and reward history are encoded in the striatum during dynamic decision making. Our predictions
highlight the potential importance of hemispheric asymmetry in striatal dopamine, SPN and PKA activity in
action selection, motor behavior and stochasticity of choice. We will further test these predictions using use
time locked perturbations of activity to understand the causal relationship of these signals to ongoing and
future behavior.

## Key facts

- **NIH application ID:** 9993584
- **Project number:** 5U19NS113201-02
- **Recipient organization:** HARVARD MEDICAL SCHOOL
- **Principal Investigator:** Linda E Wilbrecht
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $777,821
- **Award type:** 5
- **Project period:** 2019-08-15 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9993584

## Citation

> US National Institutes of Health, RePORTER application 9993584, The function of dopamine and striatal neurons in guiding behavior in uncertain environments (5U19NS113201-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9993584. Licensed CC0.

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