# Training program in computational approaches to brain and behavior

> **NIH NIH R90** · NEW YORK UNIVERSITY · 2024 · $326,116

## Abstract

PROGRAM SUMMARY
The Training Program in Computational Neuroscience (TPCN) will support integrated undergraduate and
graduate training in computational neuroscience at New York University. The program will be hosted by the
Center for Neural Science (CNS) and the Cognition and Perception (C&P) program in the Department of
Psychology, reflecting the dual roles of brain and behavior. The TPCN program faculty consist of 24 highly
productive PIs. The TPCN will be a continuation of the NIH-funded program run successfully at NYU from 2016
to 2021, which trained 24 undergraduate and 12 predoctoral students and built an infrastructure of community
activities. The TPCN fits well with NYU’s strengths: a) NYU is one of a few universities with a critical mass of
computational neuroscientists, and NYU has had a Sloan-Swartz Center for Theoretical Neuroscience since
1994 b) In the past year alone, the two participating departments have hired four primarily
computational/theoretical faculty; c) CNS established an undergraduate major in neuroscience as early as
1992; d) program faculty have a strong track record of wide-ranging collaborations as well as of co-mentoring
predoctoral students.
Each trainee in the TPCN will complete a year of coursework, laboratory research, and TPCN-specific
professional development activities, which include skill tutorials, orientation on the next career stage,
workshopping each other’s writings and presentations, faculty openly discussing the backstories of their
careers (“Growing up in Science”), predoctoral trainees mentoring undergraduate trainees, and didactic journal
clubs preceding computational neuroscience seminars by external speakers. Together, these activities form a
comprehensive preparation for an academic career in computational neuroscience.
A major goal of the TPCN will be to increase access to and diversity in computational neuroscience
especially at the undergraduate level. This requires making hidden curriculum explicit and compensating for
students’ pre-college differences in opportunity. We will realize this through a variety of measures, including a)
holding a math boot camp preceding application to TPCN; b) providing earlier exposure to research; c)
introducing undergraduate lab rotations; d) reducing the default duration of a traineeship from 2 to 1 years,
thus offering broader access.

## Key facts

- **NIH application ID:** 10929540
- **Project number:** 5R90DA060339-02
- **Recipient organization:** NEW YORK UNIVERSITY
- **Principal Investigator:** Wei Ji Ma
- **Activity code:** R90 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $326,116
- **Award type:** 5
- **Project period:** 2023-09-15 → 2028-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10929540

## Citation

> US National Institutes of Health, RePORTER application 10929540, Training program in computational approaches to brain and behavior (5R90DA060339-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10929540. Licensed CC0.

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