Using Functional Neuroimaging and Smartphone Digital Phenotyping to Understand the Emergence of Internalizing Illness
Using Functional Neuroimaging and Smartphone Digital Phenotyping to Understand the Emergence of Internalizing Illness
批准号:
10749114
负责人:
Shannon Grogans
金额:
$4.77万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-08-01 至 2025-07-31
关键词:
AddressAdultAffectiveAmygdaloid structureAnimalsAnteriorAnxietyAnxiety DisordersAttentionBehaviorBehavioralBiologicalBlack, Indigenous, People of ColorBrain imagingCellular PhoneClinicalClinical PsychologyClinical SciencesComplexDataData CollectionDevelopmentDiagnosisDimensionsDiseaseDisease susceptibilityDistressEcological momentary assessmentEmotionalEmotional disorderEmotionsEnrollmentEnsureEthicsEtiologyEventExposure toFaceFeelingFunctional Magnetic Resonance ImagingFutureHumanImaging TechniquesIndividualInsula of ReilInterviewLifeLinkMarylandMeasuresMediatorMental DepressionMental disordersMentorsModelingMoodsMorbidity - disease rateNeurobiologyNeurosciences ResearchNeurotic DisordersPanicPathologyPathway interactionsPatient Self-ReportPerceptionPhenotypeProductivityPsychiatryPublic HealthPublicationsQuestionnairesRecurrenceResearchResearch EthicsRiskRisk FactorsRoleSafetySamplingSelf MedicationShockSignal TransductionSocial isolationSocial supportStressStructureSymptomsTestingTrainingVulnerable PopulationsWithdrawalWorkadvanced analyticsanalytical toolarchived databiobankbrain circuitrycareercostdigitalemerging adultethnoracialexperienceimprovedinnovationlongitudinal, prospective studymHealthnegative moodneuralneuroimagingpreventprogramsprospectivepsychosocialracial diversityrecruitsexskillssocialtargeted treatmenttheoriestherapeutic developmenttherapy development
中文摘要
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英文摘要
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 research ethics; and for
developing the cutting-edge research program, professional skills, and publication record necessary to flourish
as an independent clinical affective neuroscientist.
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