# From Networks to the Real World: Integrating Neural and Autonomic Processes of Loss

> **NIH NIH K23** · UNIVERSITY OF SOUTHERN CALIFORNIA · 2021 · $178,999

## Abstract

PROJECT SUMMARY/ABSTRACT
Major depressive disorder (MDD) is a prevalent and debilitating disorder that is characterized by high levels of
negative affect (NA). One mechanism that may serve as a phenotype for depression risk is impaired cognitive
control of NA following loss, which is also linked to atypical parasympathetic responses to loss. The Candidate
will extend his background in cognitive and affective risk factors for MDD to examine the neural networks
supporting cognitive control and affect regulation integrating an RDoC loss construct across multiple
modalities. This will develop his mechanistic understanding and expertise in interactions between cognitive and
affective systems that underlie dysfunctional self-regulation in depression. The Candidate will learn to: 1)
evaluate task-based activity and interactions between intrinsic connectivity networks supporting cognitive control
and emotion processing (Training Aim 1 (TA1)); 2) integrate multi-modal, multi-level data and learn the
advanced statistical modeling necessary to dimensionally link fMRI to parasympathetic and affective responses
(TA2). In addition, in the latter years of the award, the candidate will learn to use the methodology of EMA and
ambulatory parasympathetic assessment to link neural networks that support the cognitive control of emotion
to lab and real-world affective/physiological regulation (TA3). In line with these training aims, the Candidate's
short-term career goals are to understand the neural networks underlying the cognitive control of emotion, and
to test the ecological validity of lab-based assessments of neural and parasympathetic responses to loss for
affect regulation. This Career Development Award will allow the Candidate to advance the cognitive
neuroscience of depression with the long-term career goal of identifying cognitive and affective phenotypic risk
markers for the development and progression of mood disorders. The University of Illinois at Chicago (UIC) is
the ideal setting for the candidate's research, with ongoing development of local resources such as an
independent research-dedicated 3T scanner and one of only 22 nationwide National Network of Depression
Centers. Mentor Scott Langenecker is an expert in the cognitive and affective neuroscience of mood disorders
across the adult lifespan, a leader in RDoC research techniques, and has an established expertise in
mechanistic approaches for studying depression. The Specific Research Aims afford an excellent opportunity
for the Candidate to learn and demonstrate expertise in the necessary skills to propel him to independence.
Contextually-appropriate task-based activation in networks supporting cognitive control and emotion
processing (Specific Aim 1) will be evaluated among thirty-five young adults (ages 18-27) with a history of
MDD who are currently remitted (rMDD) and thirty-five matched healthy controls (HCs). Parasympathetic
activity and affect regulation will be assessed during a laborator...

## Key facts

- **NIH application ID:** 10248574
- **Project number:** 5K23MH112769-05
- **Recipient organization:** UNIVERSITY OF SOUTHERN CALIFORNIA
- **Principal Investigator:** Jonathan P Stange
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $178,999
- **Award type:** 5
- **Project period:** 2017-09-13 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10248574

## Citation

> US National Institutes of Health, RePORTER application 10248574, From Networks to the Real World: Integrating Neural and Autonomic Processes of Loss (5K23MH112769-05). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10248574. Licensed CC0.

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