# Dynamic brain representations underlying emotional experience

> **NIH NIH R01** · DARTMOUTH COLLEGE · 2021 · $675,907

## Abstract

Emotions play a critical role in organizing human experience and behavior, and emotion dysregulation lies at the
heart of psychopathology and functional impairment across disorders. To measure and understand emotion
dysregulation, advances in understanding the fundamentals of how the brain generates and represents
emotional states are vitally needed. This proposal develops and validates models of the brain representations
that give rise to emotional states in naturalistic, narrative contexts. This will provide normative models of emotion
to ground future translational studies, measurement models for specific emotional brain representations, and
targets for interventions. We combine Functional Magnetic Resonance Imaging (fMRI), multi-dimensional
measures of behavior, and pattern recognition techniques to develop models of brain activity that characterize
and differentiate discrete categories of emotion experience (joy, anger, sadness, pride, and others) and blends
of emotion. We place particular emphasis on the predictive validity (sensitivity and specificity) and generalizability
of these models across sensory modalities, evaluative judgments, contextual narratives, and populations.
 We elicit emotional experiences in an ecologically valid paradigm using narratives (stories) experienced
via listening, reading, or watching video. We measure multiple types of emotional experience in parallel with
fMRI, using innovative collaborative filtering approaches to infer continuous moment-by-moment experience.
The resulting brain models of specific emotion categories afford several potentially transformative advantages.
Such models can (a) provide insight into which systems are necessary and sufficient for emotion generation
(Aim 1); (b) be shared and tested across studies, allowing us to evaluate their generalizability across contexts
(Aim 2); and (c) provide targets for psychological and neurological interventions (Aim 3).
 Six experiments focus on developing and validating emotional brain representations that are
generalizable across individuals, research sites (Dartmouth and Colorado), and populations (college students
and more diverse community samples). Expt. 1 develops models that predict the intensity of discrete emotional
states. Expts. 2-4 establish the context sensitivity and generalizability of these. Expt. 2 examines the role of
evaluative judgments in shaping emotional experience. Expt. 3 assesses the impact of background contextual
narratives. Expt. 4 evaluates the role of sensory processing in emotion representations. Expts. 5-6 establish
whether or not the brain models mediate emotional experiences. Expt. 5 uses cognitive appraisal and Expt. 6
uses real-time fMRI neurofeedback to manipulate emotion category-specific brain representations, testing for
causal effects of these psychological and brain manipulations on emotional experience.
 Together, these studies will yield generalizable models of the dynamic brain patterns underlying specific...

## Key facts

- **NIH application ID:** 10116182
- **Project number:** 5R01MH116026-04
- **Recipient organization:** DARTMOUTH COLLEGE
- **Principal Investigator:** Luke Joseph Chang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $675,907
- **Award type:** 5
- **Project period:** 2018-03-01 → 2022-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10116182

## Citation

> US National Institutes of Health, RePORTER application 10116182, Dynamic brain representations underlying emotional experience (5R01MH116026-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10116182. Licensed CC0.

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