# Dissecting basal ganglia circuit mechanisms underlying instrumental learning

> **NIH NIH R01** · DUKE UNIVERSITY · 2020 · $357,750

## Abstract

Summary
The basal ganglia (BG) are critical for action selection and instrumental learning. Maladaptive learning
in the BG circuits are known to result in behavior that persist despite harmful and aversive
consequences. To understand the compulsive nature of such actions and their tendency for relapse, it
is critical to elucidate the circuit mechanisms for the acquisition, reinforcement, and automatization of
learned actions. Recent results from our lab showed that the BG are not used to select actions in an
all-or-none fashion, as traditionally believed, but are necessary for the continuous generation of
movement kinematics in voluntary behavior. These results suggest a new conceptual framework for
understanding instrumental learning, allowing continuous quantification of performance as learning
occurs and the effect of reinforcement. This proposal aims to determine the role of the BG in
instrumental learning by combining wireless in vivo electrophysiology, optogenetics, 3D motion capture,
and behavioral assays from the instrumental conditioning paradigm in freely moving mice. We will
quantify continuous neural and behavioral dynamics during instrumental learning, habit formation,
extinction, and reinstatement. We will also examine the contributions of the dopaminergic reinforcement
signal. The proposed studies will elucidate how specific outcome and contingency representations can
recruit instrumental action controllers in the BG. We will manipulate and record from specific BG
circuits during initial instrumental learning and habit formation. Results from proposed studies will not
only shed light on instrumental learning and reinforcement, but also lead to quantitative characterization
of traditional categories such as goal-directed actions and stimulus-driven habits. They have important
implications for our understanding of addiction, which involve maladaptive learning in the same neural
circuits.

## Key facts

- **NIH application ID:** 9962360
- **Project number:** 5R01DA040701-05
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Henry Yin
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $357,750
- **Award type:** 5
- **Project period:** 2016-09-30 → 2021-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9962360

## Citation

> US National Institutes of Health, RePORTER application 9962360, Dissecting basal ganglia circuit mechanisms underlying instrumental learning (5R01DA040701-05). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/9962360. Licensed CC0.

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