# ENIGMA-COINSTAC: Advanced Worldwide Transdiagnostic Analysis of Valence System Brain Circuits

> **NIH NIH R01** · GEORGIA STATE UNIVERSITY · 2021 · $948,626

## Abstract

Project Summary
The Research Domain Criteria (RDoC) matrix delineates general constructs, that reflect basic dimensions of human
behavioral functioning that can range from normal to abnormal. The RDoC matrix organizes these constructs by domains
(e.g., positive valence and social processing systems) and units of analysis (i.e., from genes, to molecules, cells, circuits,
physiology, behavior, self-report, paradigms) such that they can be systematically studied at multiple levels of analysis.
Most clinical research studies, to date, have employed standardized symptom assessments, which are often disorder specific
and not directly linked to RDoC constructs. In schizophrenia (SZ), negative symptom domains, including avolition,
anhedonia, asociality, alogia, and blunted affect (5 factor model), have been studied in some detail. Recently a theoretical
mapping between negative symptom domains and RDoC constructs linked avolition, anhedonia, and avolition to positive
valence system, and alogia and flat affect to the social processes system. However, the proposed mappings between behavior
(negative symptom domains) and brain structures/circuitry have not been tested or validated; either in SZ, or in other
neuropsychiatric illnesses such as bipolar disorder (BD) or major depressive disorder (MDD). Earlier work suggested a
more parsimonious 2-factor model of negative symptoms, in which avolition, anhedonia, and asociality were linked to a
motivation and pleasure (MAP) factor, and and blunted affect andalogia linked to an expressive (EXP) factor. Of note, with
the exception of asociality, these factors appear to map onto positive valence and social processes systems in the RDoC
matrix; lending additional support to the proposed RDoC matrix structure related to negative symptoms. Mappings between
different interpretations of negative symptom domains (e.g., 5-factor and 2-factor models) and brain structures/circuitry
have also not been conducted. Leveraging the worldwide collaborative ENIGMA (Enhancing Neuro Imaging Genetics
through Meta-Analysis) consortium and the COINSTAC (Collaborative Informatics and Neuroimaging Suite Toolkit for
Anonymous Computation) computational platform, this proposal will combine neuroimaging and clinical measures of
negative symptoms across schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD), to validate
and extend the RDoC matrix representation of negative symptom domains in major mental illness. We extract joint
multimodal features for each separable (sub)construct, evaluate them for their relationship with the behavior, and then use
them in a subsequent cross-validation analysis. Subsequently, we evaluate their single subject prediction power. Through
these powerful computational methods, we will map structural, diffusion tensor imaging, and resting state functional
magnetic resonance imaging measures of brain structures/circuitry to negative symptom behavioral measures. Successful
completion of this ...

## Key facts

- **NIH application ID:** 10168645
- **Project number:** 5R01MH121246-03
- **Recipient organization:** GEORGIA STATE UNIVERSITY
- **Principal Investigator:** VINCE D CALHOUN
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $948,626
- **Award type:** 5
- **Project period:** 2019-08-02 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10168645

## Citation

> US National Institutes of Health, RePORTER application 10168645, ENIGMA-COINSTAC: Advanced Worldwide Transdiagnostic Analysis of Valence System Brain Circuits (5R01MH121246-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10168645. Licensed CC0.

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