# Training Program for Interactionist Cognitive Neuroscience (ICoN)

> **NIH NIH T32** · BROWN UNIVERSITY · 2021 · $228,070

## Abstract

Our training program for Interactionist Cognitive Neuroscience (ICoN) seeks to provide student-focused,
interdisciplinary training in computational cognitive neuroscience that integrates data from multiple scales and
levels of analysis. Transformative gains in understanding the human brain and mental health require
integration across multiple levels of analysis. Recent historic advances in genetics and cellular biology are
paving the way for understanding fundamentals of neural function. At the other end of the spectrum, methods
for imaging and stimulating human brains non-invasively have led to revolutionary advances in discovering
the macro-scale organization supporting perception, motivation, and cognition. Now, a major effort at the
`systems' level between these two scales is beginning to uncover the activity, connectivity, and computations
of neural circuits. The advent of this systems-level progress holds the promise of linking core circuit
computations to emergent human behavior and leading to detailed, transdiagnostic models of mental illness.
However, as we recently argued (Badre, Frank and Moore, 2015 Neuron), fulfilling this promise requires
making direct links between circuit-level computation and the emergent function of the human system. We
believe that integrating systems- and human neuroscience in this way demands a systematic approach built
on two key strategies. First, formal computational models must be used to provide principled links between
levels of analysis; and, second, complementary methods must be applied, and in the ideal case parallel
human and non-human studies conducted in coordination. Achieving these aims requires a new generation of
scientists that can take full advantage of multiple techniques and data sources, and who are deeply versed in
computational theory. Traditional neuroscience training relies on an apprenticeship model that limits students
to a single lab and level of inquiry. Thus, a specialized training program is required to specifically equip
neuroscientists for this `Interactionist' approach. ICoN will provide this training emphasizing the two tenets:
I. Computation is key to translating between levels. Students must be rigorously quantitatively
trained in formal theory. A close corollary is that they must be fluent in the advanced analysis methods
necessary for cross-level integration (e.g., machine learning).
II. Next-generation scholars must have expertise at multiple levels. Students must be trained to use
and integrate multiple methods and data sources. Further, they must have the skills (and courage) to pursue
ideas to their next most logical step, to be question driven and not technique limited. Students will be trained
to conduct integrative research projects across domains such as human cognitive neuroscience, systems
neuroscience, and computational neuroscience.

## Key facts

- **NIH application ID:** 10161832
- **Project number:** 5T32MH115895-03
- **Recipient organization:** BROWN UNIVERSITY
- **Principal Investigator:** David Badre
- **Activity code:** T32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $228,070
- **Award type:** 5
- **Project period:** 2019-07-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10161832

## Citation

> US National Institutes of Health, RePORTER application 10161832, Training Program for Interactionist Cognitive Neuroscience (ICoN) (5T32MH115895-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10161832. Licensed CC0.

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