R01MH125958
Project Grant
Overview
Grant Description
Optimized Affective Computing Measures of Social Processes and Negative Valence in Youth Psychopathology - Abstract
Difficulties with emotion expression and social behavior characterize multiple psychiatric conditions and negatively impact child development. However, existing measurement tools for indexing social-emotional function are imprecise and subjective, or require specialized training that is costly and time-intensive, prohibiting widespread implementation.
The imprecision of existing tools has a major negative impact not only on research, but on the ability to assess and treat individuals with mental health concerns – especially among underserved and under-resourced populations. Here, we propose to address this problem by quantifying social and emotional behavior using novel biobehavioral markers derived from computer vision (facial expression analysis) and computational linguistics (social/sentiment analysis).
Our team has successfully used these markers to predict the presence of Autism Spectrum Disorder (ASD) with 91% accuracy. In this proposal, we determine the extent to which our markers can serve as continuous measures of social behavior and negative emotion to advance clinical phenotyping and interventions.
The proposal brings together two high-bandwidth clinical research programs at the Children's Hospital of Philadelphia and Baylor College of Medicine to collect data on 750 adolescents (ages 12-17 inclusive) with ASD, a primary anxiety or depressive disorder, or without any developmental/psychiatric condition.
At a single assessment, all youth will participate in an extensive clinical phenotyping battery consisting of validated clinical interviews and child-/parent-report scales assessing converging and diverging mental health constructs, and three tasks eliciting positive/negative emotion, social stress, and mild frustration.
A subsample of 150 adolescents will be reassessed 6-10 weeks later to allow retest/stability analyses. A novel camera apparatus will capture naturalistic synchronized verbal and nonverbal signals from dyads.
Our analytic approach combines state-of-the-art machine learning, computational linguistics, and computer vision – including facial emotion recognition methods that rival several commonly used alternatives.
The ultimate goal of this proposal is to develop valid and objective measures of the social and negative valence systems using novel biobehavioral markers in a large transdiagnostic sample of youth. Secondary goals are to develop easy-to-follow methods to widely disseminate our tools and procedures, and to characterize individual variability in these key RDoC metrics by age, gender, race/ethnicity, and diagnosis.
The achievement of these goals will provide researchers with sorely needed measures of social and emotional behavior, and provide clinicians with a new set of tools for identifying and tracking youth in need of mental health treatment.
Difficulties with emotion expression and social behavior characterize multiple psychiatric conditions and negatively impact child development. However, existing measurement tools for indexing social-emotional function are imprecise and subjective, or require specialized training that is costly and time-intensive, prohibiting widespread implementation.
The imprecision of existing tools has a major negative impact not only on research, but on the ability to assess and treat individuals with mental health concerns – especially among underserved and under-resourced populations. Here, we propose to address this problem by quantifying social and emotional behavior using novel biobehavioral markers derived from computer vision (facial expression analysis) and computational linguistics (social/sentiment analysis).
Our team has successfully used these markers to predict the presence of Autism Spectrum Disorder (ASD) with 91% accuracy. In this proposal, we determine the extent to which our markers can serve as continuous measures of social behavior and negative emotion to advance clinical phenotyping and interventions.
The proposal brings together two high-bandwidth clinical research programs at the Children's Hospital of Philadelphia and Baylor College of Medicine to collect data on 750 adolescents (ages 12-17 inclusive) with ASD, a primary anxiety or depressive disorder, or without any developmental/psychiatric condition.
At a single assessment, all youth will participate in an extensive clinical phenotyping battery consisting of validated clinical interviews and child-/parent-report scales assessing converging and diverging mental health constructs, and three tasks eliciting positive/negative emotion, social stress, and mild frustration.
A subsample of 150 adolescents will be reassessed 6-10 weeks later to allow retest/stability analyses. A novel camera apparatus will capture naturalistic synchronized verbal and nonverbal signals from dyads.
Our analytic approach combines state-of-the-art machine learning, computational linguistics, and computer vision – including facial emotion recognition methods that rival several commonly used alternatives.
The ultimate goal of this proposal is to develop valid and objective measures of the social and negative valence systems using novel biobehavioral markers in a large transdiagnostic sample of youth. Secondary goals are to develop easy-to-follow methods to widely disseminate our tools and procedures, and to characterize individual variability in these key RDoC metrics by age, gender, race/ethnicity, and diagnosis.
The achievement of these goals will provide researchers with sorely needed measures of social and emotional behavior, and provide clinicians with a new set of tools for identifying and tracking youth in need of mental health treatment.
Funding Goals
THE MISSION OF THE NATIONAL INSTITUTE OF MENTAL HEALTH (NIMH) IS TO TRANSFORM THE UNDERSTANDING AND TREATMENT OF MENTAL ILLNESSES THROUGH BASIC AND CLINICAL RESEARCH, PAVING THE WAY FOR PREVENTION, RECOVERY, AND CURE. IN MAY 2020, NIMH RELEASED ITS NEW STRATEGIC PLAN FOR RESEARCH. THE NEW STRATEGIC PLAN BUILDS ON THE SUCCESSES OF PREVIOUS NIMH STRATEGIC PLANS BY PROVIDING A FRAMEWORK FOR SCIENTIFIC RESEARCH AND EXPLORATION, AND ADDRESSING NEW CHALLENGES IN MENTAL HEALTH. THE NEW STRATEGIC PLAN OUTLINES FOUR HIGH-LEVEL GOALS: GOAL 1: DEFINE THE BRAIN MECHANISMS UNDERLYING COMPLEX BEHAVIORS GOAL 2: EXAMINE MENTAL ILLNESS TRAJECTORIES ACROSS THE LIFESPAN GOAL 3: STRIVE FOR PREVENTION AND CURES GOAL 4: STRENGTHEN THE PUBLIC HEALTH IMPACT OF NIMH-SUPPORTED RESEARCH THESE FOUR GOALS FORM A BROAD ROADMAP FOR THE INSTITUTE'S RESEARCH PRIORITIES OVER THE NEXT FIVE YEARS, BEGINNING WITH THE FUNDAMENTAL SCIENCE OF THE BRAIN AND BEHAVIOR, AND EXTENDING THROUGH EVIDENCE-BASED SERVICES THAT IMPROVE PUBLIC HEALTH OUTCOMES. THE INSTITUTE'S OVERALL FUNDING STRATEGY IS TO SUPPORT A BROAD SPECTRUM OF INVESTIGATOR-INITIATED RESEARCH IN FUNDAMENTAL SCIENCE, WITH INCREASING USE OF INSTITUTE-SOLICITED INITIATIVES FOR APPLIED RESEARCH WHERE PUBLIC HEALTH IMPACT IS A SHORT-TERM MEASURE OF SUCCESS. THE NEW STRATEGIC PLAN ALSO ADDRESSES A NUMBER OF CROSS-CUTTING THEMES THAT ARE RELEVANT TO ALL RESEARCH SUPPORTED BY NIMH, THESE THEMES HIGHLIGHT AREAS WHERE NIMH-FUNDED SCIENCE MAY HAVE THE GREATEST IMPACT, BRIDGE GAPS, AND OFFER NOVEL APPROACHES TO ACCELERATE ADVANCES IN MENTAL HEALTH RESEARCH. FOR EXAMPLE, NIMH VALUES A COMPREHENSIVE RESEARCH AGENDA THAT TAKES AN INCLUSIVE APPROACH THAT ENSURES RESEARCH INTERESTS ARE VARIED, MAINTAIN DIVERSE PARTICIPATION AND PARTNERSHIPS, AND ACHIEVE RESEARCH GOALS ACROSS MULTIPLE TIMEFRAMES. THIS INCLUDES DIVERSE METHODOLOGIES, TOOLS, AND MODELS, RESEARCH ADDRESSING COMPLEX BASIC, TRANSLATIONAL, AND APPLIED QUESTIONS, RESEARCH INCLUDING BOTH SEXES AND, AS APPROPRIATE, GENETIC BACKGROUND, AND, PARTICIPANTS FROM DIVERSE RACIAL AND ETHNIC BACKGROUNDS, AND ACROSS GENDER IDENTITIES, GEOGRAPHICAL CONTEXT, SOCIOECONOMIC STATUS, NEUROTYPE, AND AGE OFFERING THE BEST POSSIBLE REPRESENTATION, FOR THE BROADEST NUMBER OF INDIVIDUALS WHO MAY ULTIMATELY BENEFIT FROM THESE SCIENTIFIC ADVANCES. TO ACCOMPLISH THE GOALS OUTLINED IN THE NEW STRATEGIC PLAN, NIMH WILL SUPPORT RESEARCH THAT AIMS: TO CHARACTERIZE THE GENOMIC, MOLECULAR, CELLULAR, AND CIRCUIT COMPONENTS CONTRIBUTING TO BRAIN ORGANIZATION AND FUNCTION, TO IDENTIFY THE DEVELOPMENTAL, FUNCTIONAL, AND REGULATORY MECHANISMS RELEVANT TO COGNITIVE, AFFECTIVE, AND SOCIAL DOMAINS, ACROSS UNITS OF ANALYSIS, AND, TO GENERATE AND VALIDATE NOVEL TOOLS, TECHNIQUES, AND MEASURES TO QUANTIFY CHANGES IN THE ACTIVITY OF MOLECULES, CELLS, CIRCUITS, AND CONNECTOMES. TO DISCOVER GENE VARIANTS AND OTHER GENOMIC ELEMENTS THAT CONTRIBUTE TO THE DEVELOPMENT OF MENTAL ILLNESSES IN DIVERSE POPULATIONS, TO ADVANCE OUR UNDERSTANDING OF THE COMPLEX ETIOLOGY OF MENTAL ILLNESSES USING MOLECULAR EPIDEMIOLOGIC APPROACHES THAT INCORPORATE INDIVIDUAL GENETIC INFORMATION IN LARGE COHORTS, TO ELUCIDATE HOW HUMAN GENETIC VARIATION AFFECTS THE COORDINATION OF MOLECULAR, CELLULAR, AND PHYSIOLOGICAL NETWORKS SUPPORTING HIGHER-ORDER FUNCTIONS AND EMERGENT PROPERTIES OF NEUROBIOLOGICAL SYSTEMS, AND, TO DEVELOP NOVEL TOOLS AND TECHNIQUES FOR THE ANALYSIS OF LARGE-SCALE GENETIC, MULTI-OMIC DATA AS IT APPLIES TO MENTAL HEALTH. TO UTILIZE CONNECTOMIC APPROACHES TO IDENTIFY BRAIN NETWORKS AND CIRCUIT COMPONENTS THAT CONTRIBUTE TO VARIOUS ASPECTS OF MENTAL FUNCTION AND DYSFUNCTION, TO DETERMINE THROUGH BRAIN-WIDE ANALYSIS HOW CHANGES IN THE PHYSIOLOGICAL PROPERTIES OF MOLECULES, CELLS, AND CIRCUITS CONTRIBUTE TO MENTAL ILLNESSES, TO DEVELOP MOLECULAR, CELLULAR, AND CIRCUIT-LEVEL BIOMARKERS OF IMPAIRED NEURAL FUNCTION IN HUMANS, AND, TO DEVELOP INNOVATIVE TECHNOLOGIES, INCLUDING NEW IMAGING, COMPUTATIONAL, PHARMACOLOGICAL, AND GENETIC TOOLS TO INTERROGATE AND MODULATE CIRCUIT ACTIVITY AND STRUCTURE ALTERED IN MENTAL ILLNESSES. TO ELUCIDATE THE MECHANISMS CONTRIBUTING TO THE TRAJECTORIES OF BRAIN DEVELOPMENT AND BEHAVIOR, AND, TO CHARACTERIZE THE EMERGENCE AND PROGRESSION OF MENTAL ILLNESSES, AND IDENTIFYING SENSITIVE PERIODS FOR OPTIMAL INTERVENTION. TO DETERMINE EARLY RISK AND PROTECTIVE FACTORS, AND RELATED MECHANISMS, TO SERVE AS NOVEL INTERVENTION GROUPS, AND, TO DEVELOP RELIABLE AND ROBUST BIOMARKERS AND ASSESSMENT TOOLS TO PREDICT ILLNESS ONSET, COURSE, AND ACROSS DIVERSE POPULATIONS. TO DEVELOP NOVEL INTERVENTIONS USING A MECHANISM-INFORMED, EXPERIMENTAL THERAPEUTICS APPROACH, AND, TO DEVELOP AND IMPLEMENT MEASUREMENT STRATEGIES TO FACILITATE MECHANISM-BASED INTERVENTION DEVELOPMENT AND TESTING. TO INVESTIGATE PERSONALIZED INTERVENTION STRATEGIES ACROSS DISEASE PROGRESSION AND DEVELOPMENT, AND, TO DEVELOP AND REFINE COMPUTATIONAL APPROACHES AND RESEARCH DESIGNS THAT CAN BE USED TO INFORM AND TEST PERSONALIZED INTERVENTIONS. TO DEVELOP AND TEST APPROACHES FOR ADAPTING, COMBINING, AND SEQUENCING INTERVENTIONS TO ACHIEVE THE GREATEST IMPACT ON THE LIVES AND FUNCTIONING OF PERSONS SEEKING CARE, TO CONDUCT EFFICIENT PRAGMATIC TRIALS THAT EMPLOY NEW TOOLS TO RAPIDLY IDENTIFY, ENGAGE, ASSESS, AND FOLLOW PARTICIPANTS IN THE CONTEXT OF ROUTINE CARE, AND, TO ENHANCE THE PRACTICAL RELEVANCE OF EFFECTIVENESS RESEARCH VIA DEPLOYMENT-FOCUSED, HYBRID, EFFECTIVENESS-IMPLEMENTATION STUDIES. TO EMPLOY ASSESSMENT PLATFORMS WITHIN HEALTHCARE SYSTEMS TO ACCURATELY ASSESS THE DISTRIBUTION AND DETERMINANTS OF MENTAL ILLNESSES AND TO INFORM STRATEGIES FOR IMPROVED SERVICES, TO OPTIMIZE REAL-WORLD DATA COLLECTION SYSTEMS TO IDENTIFY STRATEGIES FOR IMPROVING ACCESS, QUALITY, EFFECTIVENESS, AND CONTINUITY OF MENTAL HEALTH SERVICES, AND, TO COMPARE ALTERNATIVE FINANCING MODELS TO PROMOTE EFFECTIVE AND EFFICIENT CARE FOR INDIVIDUALS WITH SERIOUS EMOTIONAL DISTURBANCES AND SERIOUS MENTAL ILLNESSES. TO STRENGTHEN PARTNERSHIPS WITH KEY STAKEHOLDERS TO DEVELOP AND VALIDATE STRATEGIES FOR IMPLEMENTING, SUSTAINING, AND CONTINUOUSLY IMPROVE EVIDENCE-BASED PRACTICES, TO BUILD MODELS TO SCALE-UP EVIDENCE-BASED PRACTICES FOR USE IN PUBLIC AND PRIVATE PRIMARY CARE, SPECIALTY CARE AND OTHER SETTINGS, AND, TO DEVELOP DECISION-SUPPORT TOOLS AND TECHNOLOGIES THAT INCREASE THE EFFECTIVENESS AND CONTINUOUS IMPROVEMENT OF MENTAL HEALTH INTERVENTIONS IN PUBLIC AND PRIVATE PRIMARY CARE, SPECIALTY CARE, AND OTHER SETTINGS. TO ADAPT, VALIDATE, AND SCALE-UP PROGRAMS CURRENTLY IN USE THAT IMPROVE MENTAL HEALTH SERVICES FOR UNDERSERVED POPULATIONS, TO DEVELOP AND VALIDATE SERVICE DELIVERY MODELS THAT PROVIDE EVIDENCE-BASED CARE FOR INDIVIDUALS THROUGHOUT THE COURSE OF MENTAL ILLNESS, TO DEVELOP AND VALIDATE SYSTEMS-LEVEL STRATEGIES USING TECHNOLOGY AND OTHER APPROACHES, TO IDENTIFY, SUPPORT, AND MONITOR THE EFFECTIVENESS OF EVIDENCE-BASED CARE THROUGHOUT THE COURSE OF ILLNESS, AND, TO DEVELOP AND VALIDATE DECISION-MAKING MODELS THAT BRIDGE MENTAL HEALTH, MEDICAL, AND OTHER CARE SETTINGS TO INTEGRATE THE APPROPRIATE CARE FOR PEOPLE WITH SERIOUS MENTAL ILLNESSES AND COMORBID MEDICAL CONDITIONS.
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Philadelphia,
Pennsylvania
191044318
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 482% from $777,357 to $4,522,502.
The Children's Hospital Of Philadelphia was awarded
Optimized Affective Computing for Youth Psychopathology
Project Grant R01MH125958
worth $4,522,502
from the National Institute of Mental Health in April 2021 with work to be completed primarily in Philadelphia Pennsylvania United States.
The grant
has a duration of 4 years 9 months and
was awarded through assistance program 93.242 Mental Health Research Grants.
The Project Grant was awarded through grant opportunity Development and Optimization of Tasks and Measures for Functional Domains of Behavior (R01 Clinical Trial Not Allowed).
Status
(Ongoing)
Last Modified 1/28/25
Period of Performance
4/2/21
Start Date
1/31/26
End Date
Funding Split
$4.5M
Federal Obligation
$0.0
Non-Federal Obligation
$4.5M
Total Obligated
Activity Timeline
Subgrant Awards
Disclosed subgrants for R01MH125958
Transaction History
Modifications to R01MH125958
Additional Detail
Award ID FAIN
R01MH125958
SAI Number
R01MH125958-1249825909
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Nonprofit With 501(c)(3) IRS Status (Other Than An Institution Of Higher Education)
Awarding Office
75N700 NIH NATIONAL INSTITUTE OF MENTAL HEALTH
Funding Office
75N700 NIH NATIONAL INSTITUTE OF MENTAL HEALTH
Awardee UEI
G7MQPLSUX1L4
Awardee CAGE
0GXU0
Performance District
PA-03
Senators
Robert Casey
John Fetterman
John Fetterman
Budget Funding
| Federal Account | Budget Subfunction | Object Class | Total | Percentage |
|---|---|---|---|---|
| National Institute of Mental Health, National Institutes of Health, Health and Human Services (075-0892) | Health research and training | Grants, subsidies, and contributions (41.0) | $1,549,569 | 73% |
| Office of the Director, National Institutes of Health, Health and Human Services (075-0846) | Health research and training | Grants, subsidies, and contributions (41.0) | $583,720 | 27% |
Modified: 1/28/25