# Computational neuroimaging of reward in post-trauma psychopathology

> **NIH NIH K23** · UNIVERSITY OF TEXAS AT AUSTIN · 2020 · $191,046

## Abstract

Project Abstract
 This is a proposal for a K23 Mentored Patient-Oriented Research Career Development Award for
Gregory A. Fonzo, Ph.D. entitled: Computational neuroimaging of reward in post-trauma psychopathology.
The K23 award would allow Dr. Fonzo to gain proficiency in: 1) reward processing and reinforcement learning
theory, paradigms, and analysis; 2) computational approaches to modeling behavior and brain function; 3)
basic and systems neuroscience; 4) mechanisms of treatment; and 5) manuscript/grant writing, professional
development, and responsible conduct of research. All of the training and research will be conducted at
Stanford University and its close affiliate, the Veteran's Affairs Medical Center in Palo Alto, which provides
access to abundant intellectual and physical resources. The goal of this project is to better understand
diminished positive affect in post-trauma psychopathology (PTP) through characterizing reward processing in a
computational framework. Diminished positive affect in PTP is an important area for study, as these symptoms
confer worse treatment outcomes, poorer quality of life, and greater levels of disability. Positive affect refers to
the frequency and intensity with which an individual subjectively experiences positive valence emotions. The
study of reward processing has been utilized for decades in animals and humans to elicit positive emotion and
appetitive behavior, and reward processing reliably recruits neural substrates implicated in positive affect.
Thus, this experimental framework is the ideal entrance point to begin study of diminished positive affect in
PTP. Little work is being done in this area, and the need for a better understanding of the behavioral and
neural bases of these symptoms is profound. The central hypothesis to be tested is the development of PTP
perturbs reward circuit function, information flow, and subsequent behavioral processing of rewarding stimuli,
which promotes diminished positive affect and impairs functioning through disrupting the reinforcement
learning that guides and optimizes behavior. The current study aims to: 1) Identify reward circuit abnormalities
in PTP during reward processing and at rest; 2) Understand how information is processed differently in PTP
during reinforcement learning and how this is instantiated in neural circuits; and 3) Identify how reward
processing abnormalities relate to symptoms of diminished positive affect. The PI plans to gain proficiency in
proposal domains through: 1) tutorials and meetings with mentors; 2) intensive workshops on modeling
information flow within neural circuits and building computational models of reward behavior; 3) formal
coursework; 4) attendance of professional meetings; 5) practical application of skills to research data; and 6)
planned submission of grant applications and manuscripts. Insights from the proposed work will improve our
understanding of the brain processes underlying diminished positive affect in PTP, w...

## Key facts

- **NIH application ID:** 9930682
- **Project number:** 5K23MH114023-04
- **Recipient organization:** UNIVERSITY OF TEXAS AT AUSTIN
- **Principal Investigator:** Gregory Fonzo
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $191,046
- **Award type:** 5
- **Project period:** 2018-12-01 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9930682

## Citation

> US National Institutes of Health, RePORTER application 9930682, Computational neuroimaging of reward in post-trauma psychopathology (5K23MH114023-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9930682. Licensed CC0.

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