# NRSA Training Grant in Quantitative Neuroscience

> **NIH NIH T32** · PRINCETON UNIVERSITY · 2024 · $491,130

## Abstract

This proposal is for the renewal of a predoctoral and postdoctoral Quantitative Neuroscience Training Program
(QNTP) at Princeton University. Neuroscience research is becoming increasingly quantitative. Formal theoretical
techniques are essential for understanding how complex, large-scale interactions between neurons give rise to
thought and behavior, and advanced quantitative methods of data analysis are necessary for addressing the
increasingly large, multidimensional data sets generated by modern brain imaging techniques (e.g., multiunit
recording, fMRI). These methods are also necessary for future progress to be made in understanding,
diagnosing, treating and, ultimately, curing brain disturbances that give rise to psychiatric disorders.
Unfortunately, the mathematical and computational skills required to address these needs are not a focus of
standard neuroscience curricula. Princeton’s QNTP is designed to address this need, by providing the next
generation of neuroscientists with the necessary mathematical and computational skills for measuring, analyzing,
and modeling brain function. The establishment of the QNTP sparked several developments at Princeton, that
(in turn) have accelerated the pace at which the goals of the QNTP are being met. By bringing Princeton’s
neuroscientists together with faculty in Physics, Mathematics, Computer Science and Engineering, the QNTP
helped to spur the formation of the Princeton Neuroscience Institute (PNI) in 2005. The QNTP also helped to
inspire the formation (in 2008) of PNI’s free-standing PhD Program in Neuroscience, which strongly emphasizes
classroom and laboratory training in basic quantitative and computational methods during its first two years.
These developments have made it possible for us to refocus the QNTP from its original purpose (providing a
foundation in quantitative neuroscience for trainees who are starting out in this area) to providing advanced
training in quantitative neuroscience. Specifically, we will take the most quantitatively-focused subset of our
predoctoral and postdoctoral trainees and provide them with the additional tools and training that they need to
excel in computational neuroscience research. This training will be accomplished via advanced quantitative and
computational neuroscience elective courses that were developed for the QNTP and are taught by leaders in
the field, as well as participation in research seminars, journal clubs, and career development activities that are
designed to deepen the trainees’ knowledge and bolster community among the trainees. PNI faculty have made
seminal contributions to quantitative neuroscience, ranging from information-theoretic analyses of neuronal
spiking and dynamical systems analysis of decision-making to multivariate decoding of human neuroimaging
data. The QNTP has been specifically formulated to bring predoctoral and postdoctoral trainees into contact with
this expertise and, through this, to catalyze their transformation ...

## Key facts

- **NIH application ID:** 10849231
- **Project number:** 2T32MH065214-21A1
- **Recipient organization:** PRINCETON UNIVERSITY
- **Principal Investigator:** Nathaniel Douglass Daw
- **Activity code:** T32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $491,130
- **Award type:** 2
- **Project period:** 2002-07-01 → 2029-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10849231

## Citation

> US National Institutes of Health, RePORTER application 10849231, NRSA Training Grant in Quantitative Neuroscience (2T32MH065214-21A1). Retrieved via AI Analytics 2026-06-10 from https://api.ai-analytics.org/grant/nih/10849231. Licensed CC0.

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