# Reinforcement Mechanisms for Learning Vocal Behaviors - Renewal - 1

> **NIH NIH R01** · UT SOUTHWESTERN MEDICAL CENTER · 2024 · $592,797

## Abstract

PROJECT SUMMARY
How skilled behaviors like speech and language are actively maintained throughout life is not well understood
and still poorly studied. Our research program uses songbird vocal learning and vocal production to understand
how forebrain circuits and reinforcement mechanisms are used to acquire and then maintain learned
vocalizations. Our research has helped demonstrate that midbrain dopaminergic circuits bidirectionally guide
learned changes in song in a manner consistent with them functioning as reward prediction error signals
envisaged by reinforcement models. Building from this, we turn our attention to understand how the basal ganglia
and dopaminergic circuits support the lifelong maintenance of behavior. We hypothesize that predictive
dopaminergic signals safeguard the lifelong maintenance of natural behaviors. Our initial studies provide a
glimpse at central mechanisms sufficient to initiate the long term decrystallization of a previously learned and
internally reinforced natural behavior. Using a variety of cutting-edge approaches that we have optimized for
circuit interrogation in songbirds, we aim to dissect the cellular and synaptic mechanisms associated with song
decrystallization, and the role of circuit nodes downstream of dopaminergic pathways in song maintenance and
song decrystallization. In the first aim we will test the role of predictive dopaminergic signals in the long-term
maintenance of adult zebra finch song using optogenetic manipulations and functional imaging of dopamine
activity in adult animals. In the second aim we will examine the cellular and synaptic mechanisms of song
decrystallization. In the third aim we will test the role of pallidal-thalamic circuits downstream of dopaminergic
striatal pathways in the implementation and rescue of song decrystallization. Together, these studies can provide
fundamental and mechanistic insights into how the brain continuously monitors and updates behavior to maintain
expert performance and reveal what happens when this process goes awry.

## Key facts

- **NIH application ID:** 10935985
- **Project number:** 5R01NS102488-07
- **Recipient organization:** UT SOUTHWESTERN MEDICAL CENTER
- **Principal Investigator:** TODD F ROBERTS
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $592,797
- **Award type:** 5
- **Project period:** 2018-04-01 → 2028-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10935985

## Citation

> US National Institutes of Health, RePORTER application 10935985, Reinforcement Mechanisms for Learning Vocal Behaviors - Renewal - 1 (5R01NS102488-07). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10935985. Licensed CC0.

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