# Striatal Dopamine Signals Underlying Valence-Dependent Learning

> **NIH NIH R01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2024 · $557,736

## Abstract

Project Summary
Real-life learning occurs through feedback in the form of reward or punishment. Dopamine is a key molecule in
the brain known to play a central role in learning from rewards. However, the role of these molecules in learning
from punishments, or a combination of positive and negative valence outcomes (i.e., reward and punishment),
has yet to be resolved. Parkinson’s disease and other dopamine-related disorders demonstrate deficits related
to such valence-dependent learning and these have been shown to broadly affect multiple, cognitive and motor,
forms of learning. Dopamine signals related to negative valence have recently been observed in regions lying
outside of well-known reward-related areas in the ventral striatum brain region. Parkinson’s disease is known to
produce a spatial pattern of dopamine loss in the striatum. Thus, I hypothesize that dopamine signals processing
different positive and negative valence information originate in different areas of the striatum to regulate learning.
Tools capable of multi-site recording of dopamine molecules with chronically stable performance are needed to
explore dopamine’s spatially segregated functions in valence-dependent learning. I established the tools needed
to record dopamine from multiple widely distributed sites in the striatum and over prolonged timeframes (> 1
year) to measure throughout the process of learning. Dopamine’s widely established role in learning mainly
comes from measurements in simple associative learning tasks used in rodents, which take less than a day to
learn. Here, the goal is to look at dopamine function during extended forms of learning where behaviors evolve
over the course of months by leveraging the chronic sensors I developed. Furthermore, the effect of valence on
learning has been shown to depend on task demands and complexity. Therefore, an array of learning tasks is
needed to evaluate how dopamine processes the effects of valence on learning. Tasks selected for this proposal
incorporate simple associative learning known to have a strong basis for dopamine, as well as cognitive and
motor forms of learning that are also thought to recruit dopamine based on their observed deficit in Parkinson’s
disease and other dopamine pathologies. Here, I propose to apply my chronic sensors to measure dopamine
across multiple sites in the striatum of monkeys as they learn to perform a variety of tasks probing simple
associative, cognitive, and motor functions, through a combination of positive and negative valence incentives.
Aim 1 will measure dopamine’s spatially segregated functions in valence-dependent associative learning. Aim 2
will identify the valence-specific dopamine signals recruited for more cognitively demanding, category learning.
Aim 3 will distinguish the dopamine signals subserving valence-dependent motor learning. These studies will
expand our knowledge on dopamine’s spatially distributed functions, helping to uncover how these molecules
contribut...

## Key facts

- **NIH application ID:** 10881346
- **Project number:** 1R01NS133045-01A1
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Helen N Schwerdt
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $557,736
- **Award type:** 1
- **Project period:** 2024-08-15 → 2029-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10881346

## Citation

> US National Institutes of Health, RePORTER application 10881346, Striatal Dopamine Signals Underlying Valence-Dependent Learning (1R01NS133045-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10881346. Licensed CC0.

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