Avram Holmes
Associate Professor TermAbout
Titles
Associate Professor Term
Biography
Dr. Holmes earned a Bachelors degree in psychology from Pennsylvania State University (1998), a PhD in Clinical Psychology from Harvard University (2009), and received his clinical training at the Warren Alpert Medical School of Brown University (2008-2009). Prior to joining the faculty at Yale, Dr. Holmes completed a postdoctoral fellowship at the Harvard University Center for Brain Science (2009-2012) and served as an Instructor in Psychiatry at Harvard Medical School (2012-2014).
Last Updated on April 07, 2025.
Research
Publications
2026
Neuroanatomy reflects individual variability in impulsivity in youth
Dhamala E, Christensen E, Hanson J, Ricard J, Arcaro N, Bhola S, Wiersch L, Brosch K, Yeo B, Holmes A, Yip S. Neuroanatomy reflects individual variability in impulsivity in youth. Molecular Psychiatry 2026, 1-15. PMID: 41876706, DOI: 10.1038/s41380-026-03526-2.Peer-Reviewed Original ResearchAdolescent Brain Cognitive DevelopmentNeural basisImpulsivity measuresSelf-report impulsivity measuresSelf-reported impulsivityGray matter volumeSample of youthImpulsivity dimensionsEmotion regulationDefault modeVentral attentionMatter volumeIndividual differencesPsychiatric illnessSix-year follow-upVisual networkNeuroanatomical featuresCognitive developmentNeural circuitsSex effectsCortical thicknessTwo-year follow-upBrain stem structuresDevelopmental time pointsBehavioral research
2025
Inferring intrinsic neural timescales using optimal control theory
Kim J, Betzel R, Beyh A, Howell A, Kuceyeski A, Larsen B, Seguin C, Zhang X, Holmes A, Parkes L. Inferring intrinsic neural timescales using optimal control theory. Nature Communications 2025, 16: 11639. PMID: 41298426, PMCID: PMC12748979, DOI: 10.1038/s41467-025-66542-w.Peer-Reviewed Original ResearchIntrinsic neural timescalesNetwork control theoryNeural timescalesNeurobiological measuresTemporal evolutionBrain regionsWhole-brain activityMeasures of cognitionFunctional neuroimaging dataBrain connectivityBrain structuresNeuroimaging dataIntrinsic dynamicsBrain statesTimescalesBrainBiophysical realismOptimal control theoryTheoryMeasurement of gene expressionDynamicsConnectomeNeurobiologyCognitionRegionFrom big to small: Emerging methods for enhancing precision psychiatry through transfer learning
Wang Y, Holmes A, Yeo B, Yip S. From big to small: Emerging methods for enhancing precision psychiatry through transfer learning. Biological Psychiatry 2025 PMID: 41173199, PMCID: PMC12704548, DOI: 10.1016/j.biopsych.2025.10.022.Peer-Reviewed Original ResearchPrecision psychiatryGoal of precision psychiatryBrain-behavior modelsComplex clinical phenomenaNeurobiological featuresIndividual differencesNeural mechanismsSymptom profilesCognitive functionNeuroimaging dataClinical phenomenonPsychiatryLarge-scale neuroimaging datasetsNeuroimaging datasetsTreatment outcomesTransfer learningNeuroimagingClinical utilityTransfer learning approachHigh-dimensional datasetsLearningClinical settingDeep learningMachine learningGeneralizabilityDeep learning reveals that multidimensional social status drives population variation in 11,875 US participant cohort
Marotta J, Aggarwal S, Osayande N, Saltoun K, Kopal J, Holmes A, Yip S, Bzdok D. Deep learning reveals that multidimensional social status drives population variation in 11,875 US participant cohort. PLOS ONE 2025, 20: e0327729. PMID: 40802661, PMCID: PMC12349134, DOI: 10.1371/journal.pone.0327729.Peer-Reviewed Original ResearchConceptsSocial determinantsSocial determinants of healthSocioeconomic statusDeterminants of healthMaterial povertySocial stratificationAdolescent Brain Cognitive DevelopmentSM StudySocial statusMinoritized groupsHealthy home environmentPopulation variationEducational opportunitiesMental healthTiesBehavioral correlatesMultidimensional constructEthnically minoritized groupsHome environmentPovertyGeographyBehavior relationshipIndividuals of European ancestryIncomeNeighborhoodHuman populationThe Transdiagnostic Connectome Project: an open dataset for studying brain-behavior relationships in psychiatry
Chopra S, Cocuzza C, Lawhead C, Ricard J, Labache L, Patrick L, Kumar P, Rubenstein A, Moses J, Chen L, Blankenbaker C, Gillis B, Germine L, Harpaz-Rotem I, Yeo B, Baker J, Holmes A. The Transdiagnostic Connectome Project: an open dataset for studying brain-behavior relationships in psychiatry. Scientific Data 2025, 12: 923. PMID: 40456751, PMCID: PMC12130183, DOI: 10.1038/s41597-025-04895-z.Peer-Reviewed Original ResearchConceptsTask-based functional MRIHigh-resolution anatomical scansBrain-behavior relationshipsHealthy comparison groupFeatures of brain functionFunctional network organizationClinically relevant symptomsPsychiatric illnessFunctional MRINeuroimaging dataResting-stateBrain functionClinical neuroscienceCognitive AssessmentBehavioral dataConnectome ProjectAnatomical scansComparison groupDiagnostic criteriaNetwork organizationRelevant symptomsPsychiatryActivating effectIndividualsTransdiagnosticGovernance for anti-racist AI in healthcare: integrating racism-related stress in psychiatric algorithms for Black Americans
Fields C, Black C, Thind J, Jegede O, Aksen D, Rosenblatt M, Assari S, Bellamy C, Anderson E, Holmes A, Scheinost D. Governance for anti-racist AI in healthcare: integrating racism-related stress in psychiatric algorithms for Black Americans. Frontiers In Digital Health 2025, 7: 1492736. PMID: 40444183, PMCID: PMC12119476, DOI: 10.3389/fdgth.2025.1492736.Peer-Reviewed Original ResearchRacism-related stressBlack patientsBlack AmericansClinical algorithmAnti-Black racismHealthcare interventionsAnti-Black biasHealth outcomesHealth policySocioeconomic statusIntervention modelHistory of enslavementPatient outcomesCommunity membersHealthcareGenerational traumaHealthAmerica's historyBlack researchersSources of varianceClinical practiceEquitable outcomesSocial factorsRacial groupsAI governance248. Shared and Unique Lifetime Stressor Characteristics and Brain Networks Predict Adolescent Anxiety and Depression
Qu Y, Chopra S, Qu S, Cocuzza C, Labache L, Bauer C, Morfini F, Whitfield-Gabrieli S, Slavich G, Joormann J, Holmes A. 248. Shared and Unique Lifetime Stressor Characteristics and Brain Networks Predict Adolescent Anxiety and Depression. Biological Psychiatry 2025, 97: s197-s198. DOI: 10.1016/j.biopsych.2025.02.485.Peer-Reviewed Original ResearchRacialized Heteroscedasticity as a Source of Algorithmic Bias in Psychiatric Prediction Models
Fields C, Rosenblatt M, Aina J, Black C, Thind J, Jegede O, Aksen D, Assari S, Bellamy C, Anderson E, Zhou X, Holmes A, Khalifa F, Scheinost D. Racialized Heteroscedasticity as a Source of Algorithmic Bias in Psychiatric Prediction Models. Biological Psychiatry 2025, 97: s45. DOI: 10.1016/j.biopsych.2025.02.121.Peer-Reviewed Original ResearchQuantifying associations between socio-spatial factors and cognitive development in the ABCD cohort
Osayande N, Marotta J, Aggarwal S, Kopal J, Holmes A, Yip S, Bzdok D. Quantifying associations between socio-spatial factors and cognitive development in the ABCD cohort. Nature Computational Science 2025, 5: 221-233. PMID: 40114020, DOI: 10.1038/s43588-025-00774-0.Peer-Reviewed Original ResearchConceptsAdolescent Brain Cognitive Development StudyCognitive developmentUS Census dataCognitive Development StudyBayesian multilevel regressionPost-stratificationSocio-spatial factorsSociodemographic disparitiesSocioeconomic statusABCD cohortSociodemographic variablesBayesian multilevel modelsQuantify associationsInter-individual differencesMultilevel regressionPublic healthMultilevel modelsCensus dataInterpretation of model predictionsDemographic groupsDevelopment studiesHolistic explanationHomogeneous representationModeling frameworkMounting demandProtective role of parenthood on age-related brain function in mid- to late-life
Orchard E, Chopra S, Ooi L, Chen P, An L, Jamadar S, Yeo B, Rutherford H, Holmes A. Protective role of parenthood on age-related brain function in mid- to late-life. Proceedings Of The National Academy Of Sciences Of The United States Of America 2025, 122: e2411245122. PMID: 39999172, PMCID: PMC11892684, DOI: 10.1073/pnas.2411245122.Peer-Reviewed Original ResearchConceptsBrain functionFunctional connectivityPatterns of brain functionAssociated with higher connectivityConsistent with animal modelsBrain structuresCaregiving environmentAssociated with patternsAge-related alterationsBrain healthAging trajectoriesLate-lifeSpatial topographyAdult brainImpact of caregivingBrainPreliminary findingsHuman parentingImpact of ageCaregiving experienceChildrenCaregiversHigher connectivityEffect of parenthoodOne-body