Dissecting basal ganglia circuit mechanisms underlying instrumental learning

NIH RePORTER · NIH · R01 · $357,750 · view on reporter.nih.gov ↗

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
DUKE UNIVERSITY
Principal Investigator
Henry Yin
Activity code
R01
Funding institute
NIH
Fiscal year
2020
Award amount
$357,750
Award type
5
Project period
2016-09-30 → 2021-06-30