# Postsynaptic mechanisms underlying negative prediction error

> **NIH NIH R21** · UNIVERSITY OF CHICAGO · 2022 · $238,576

## Abstract

ABSTRACT
 The role of the dopamine system in reward has been well established. Whether dopaminergic mechanisms
may underlie reinforcement learning or incentive motivation has been a central issue in the field. Evidence that
supports the reinforcement learning hypothesis mostly come from recordings of dopamine neuron firing or
dopamine release that are often temporally correlated with prediction error. In contrast, causal evidence that
supports the incentive motivation hypothesis mostly come from pharmacological manipulations of
dopaminergic signaling that often show altered motivation in reward seeking. One study that stands out is Roy
Wise’s 1978 study that used dopamine antagonist and unambiguously demonstrated that decreased
dopaminergic signaling is sufficient in causing extinction learning. It is often cited as one of the best causal
evidence that supports reinforcement learning but not incentive motivation hypothesis. However, a number of
questions remain unanswered. Is it dose dependent? Is it receptor specific? Is it post-synaptic signaling
pathway specific? Does such manipulation represent negative prediction error?
 To address these questions, the present application will employ operant conditioning paradigms similar to
what’s used in the Wise paper and test the following hypothesis: lack of dopaminergic signaling--> negative
prediction error--> lack of dopamine D2 receptor activation-->lack of inhibition of adenylyl cyclase 5 (AC5) -->
elevated cAMP in D2 striatal neurons-->extinction learning.
 In Aim 1, we will use D2 antagonist and use Gs DREADD expressed in D2 striatal neurons to cause
extinction (to test sufficiency). We will also use AC5 knockout mice, AC5 inhibitor and Gi DREADD expressed
in D2 striatal neurons to prevent extinction (to test necessity).
 The objective of Aim 1 is to establish that “D2-AC5-cAMP elevation” is indeed necessary and sufficient in
causing extinction learning using natural reward. However, those studies will not demonstrate if this pathway is
in fact processing the negative prediction error signal in causing extinction learning. Aim 2 studies will use
experimentally generated phasic dip in dopamine release to test this hypothesis. In addition, we will use light
induced phasic dopamine neuron firing during no reward condition. We will test if such a manipulation will be
able to prevent extinction caused by lack of reward.

## Key facts

- **NIH application ID:** 10539883
- **Project number:** 1R21DA057073-01
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** Xiaoxi Zhuang
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $238,576
- **Award type:** 1
- **Project period:** 2022-08-15 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10539883

## Citation

> US National Institutes of Health, RePORTER application 10539883, Postsynaptic mechanisms underlying negative prediction error (1R21DA057073-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10539883. Licensed CC0.

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