# Using Functional Neuroimaging and Smartphone Digital Phenotyping to Understand the Emergence of Internalizing Illness > **NIH NIH F31** · UNIV OF MARYLAND, COLLEGE PARK · 2024 · $48,974 ## Abstract Anxiety and depression impose a staggering burden on public health and often emerge during times of stress. Yet the underlying mechanisms remain poorly understood, thwarting the development of improved treatments. While the etiology of internalizing illness is undoubtedly complex and multifactorial, emerging evidence motivates the overarching hypothesis that aberrant neural processing of Threat and Safety independently confer increased risk for internalizing illnesses. This work suggests that: (a) hyper-reactivity to Uncertain Threat anticipation increases risk, (b) deficient Safety Signaling increases risk, and (c) these associations are magnified by exposure to Negative Life Events (NLEs). Archival data from the Maryland iRisk Study provide an optimal platform for rigorously addressing these fundamental gaps. iRisk is a recently completed prospective-longitudinal study focused on a racially diverse, sex-balanced sample of emerging adults enriched for internalizing risk. At enrollment, fMRI and a well-established Threat-anticipation task were used to quantify reactivity to Uncertain and Certain Shock-Threat, as well as Safety. Reactivity to a popular emotion-perception (‘threat-related’ faces) task was also assessed. Smartphone ecological momentary assessment (EMA) was used to intensively probe daily experience at 0, 6, 24, and 30 months, providing an unprecedented multi-year assessment of mood dynamics and a first opportunity to assess the real-world significance of Threat and Safety brain circuitry. At each wave, mood, symptoms, function, and social support were also assessed. Diagnoses, dimensional symptoms, and NLEs were assessed using gold-standard interviews at 0, 15, and 30 months. These data will enable me to (1) understand the relevance of Threat and Safety circuity to the emergence of internalizing symptoms/diagnoses, (2) understand their role in the emergence of more etiologically proximal pathology- promoting feelings and behaviors in daily life, and (3) explore the relative predictive merits of a genuinely distressing Threat-anticipation task vs. a widely used Threat-perception (emotional-faces) task. Impact. Internalizing illnesses are a leading cause of human misery and morbidity. This project would provide a potentially transformative opportunity to deepen our understanding of etiology and refine clinical science theory. It would inform the development of mechanistic models in humans and animals, and provide a quantitative rationale for prioritizing new biological and psychosocial targets for therapeutics development and repurposing, including scalable mHealth approaches. This project builds on my strong computational and neuroimaging skills, my extensive experience with practical aspects of study implementation, and my preliminary experiences working with EMA data. It would provide an exceptional vehicle for training in state-of-the-art analytic approaches, EMA data collection and best-practices, internalizing illness, and resea... ## Key facts - **NIH application ID:** 10856906 - **Project number:** 5F31MH132280-02 - **Recipient organization:** UNIV OF MARYLAND, COLLEGE PARK - **Principal Investigator:** Shannon Grogans - **Activity code:** F31 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $48,974 - **Award type:** 5 - **Project period:** 2023-08-01 → 2025-07-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10856906 ## Citation > US National Institutes of Health, RePORTER application 10856906, Using Functional Neuroimaging and Smartphone Digital Phenotyping to Understand the Emergence of Internalizing Illness (5F31MH132280-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10856906. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*