# Brown Postdoctoral Training Program in Computational Psychiatry

> **NIH NIH T32** · BROWN UNIVERSITY · 2022 · $403,857

## Abstract

The goal of understanding psychiatric disorders and advancing psychiatric treatments requires basic
knowledge of not only what environmental, genetic and epigenetic factors underlie function and dysfunction,
but also how these factors alter the circuit-level computations that are the proximal neural events to behavior.
The advent of research in this area holds the promise of linking core computations of neural circuits to complex
human behavior, with the ultimate goal of developing comprehensive, multilevel transdiagnostic models of
neuropsychiatric disorders. Consequently, the emerging field of computational psychiatry is central to the
NIMH mission. Despite its importance, there are very few opportunities to pursue training in this area.
Consequently, the proposed training program seeks to take recent PhDs, with strong backgrounds in fields
such as neuroscience, engineering, applied math, and computer science, and provide them with the tools to
make important contributions to the nascent field of computational psychiatry. The proposed Training Program
in Computational Psychiatry (TPCP) will take place at Brown University where there is a critical mass of basic
researchers on the main campus and clinical researchers in the Department of Psychiatry and Human
Behavior to conduct such a training program. We propose enrolling six fellows (3 per year) in the TPCP with
the goal of training, more efficiently and effectively, nonclinical research fellows capable of collaborating with
clinical researchers to advance knowledge of psychiatric disorders and treatments. The program embraces an
apprenticeship model in which fellows work with a primary research trainer in a computational field and a
secondary research mentor in clinical psychiatry. In this apprenticeship model, the trainer works closely with
the fellow and a secondary clinical psychiatry mentor, who is conducting research in areas such as
neuroimaging, neurostimulation, and digital phenotyping. These research areas are especially conducive to
addressing important issues in computational psychiatry, whether they be model/theory-driven or data-driven.
The proposed didactic program will include both core seminars and an individualized curriculum including
fellow-selected courses in neuroscience, computer science, engineering, applied mathematics, or psychiatric
disorders. All fellows attend core seminars on grant writing, responsible conduct of research, and rigor and
reproducibility. The short-term final product is an NIH grant application on a computational psychiatry topic.
The long-term goal is to produce a new cohort of academics who can conduct research in computational
psychiatry and train the next generation of graduate students in this emerging field of inquiry.

## Key facts

- **NIH application ID:** 10388230
- **Project number:** 5T32MH126388-02
- **Recipient organization:** BROWN UNIVERSITY
- **Principal Investigator:** MICHAEL J. FRANK
- **Activity code:** T32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $403,857
- **Award type:** 5
- **Project period:** 2021-07-01 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10388230

## Citation

> US National Institutes of Health, RePORTER application 10388230, Brown Postdoctoral Training Program in Computational Psychiatry (5T32MH126388-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10388230. Licensed CC0.

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