2024
Prediction of craving across studies: A commentary on conceptual and methodological considerations when using data-driven methods
Antons S, Yip S, Lacadie C, Dadashkarimi J, Scheinost D, Brand M, Potenza M. Prediction of craving across studies: A commentary on conceptual and methodological considerations when using data-driven methods. Journal Of Behavioral Addictions 2024, 13: 695-701. PMID: 39356557, PMCID: PMC11457034, DOI: 10.1556/2006.2024.00050.Peer-Reviewed Original ResearchConceptsAddictive behaviorsDisorders due to addictive behaviorsConnectome-based predictive modelingPrediction of cravingInvestigate neural mechanismsSubstance use disordersNeural mechanismsCravingSubstance useMethodological considerationsDisordersMethodological featuresBehaviorConceptualizationCommentaryStudyFindingsSubstances
2022
Machine Learning and Prediction in Fetal, Infant, and Toddler Neuroimaging: A Review and Primer
Scheinost D, Pollatou A, Dufford A, Jiang R, Farruggia M, Rosenblatt M, Peterson H, Rodriguez R, Dadashkarimi J, Liang Q, Dai W, Foster M, Camp C, Tejavibulya L, Adkinson B, Sun H, Ye J, Cheng Q, Spann M, Rolison M, Noble S, Westwater M. Machine Learning and Prediction in Fetal, Infant, and Toddler Neuroimaging: A Review and Primer. Biological Psychiatry 2022, 93: 893-904. PMID: 36759257, PMCID: PMC10259670, DOI: 10.1016/j.biopsych.2022.10.014.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsPredicting the future of neuroimaging predictive models in mental health
Tejavibulya L, Rolison M, Gao S, Liang Q, Peterson H, Dadashkarimi J, Farruggia MC, Hahn CA, Noble S, Lichenstein SD, Pollatou A, Dufford AJ, Scheinost D. Predicting the future of neuroimaging predictive models in mental health. Molecular Psychiatry 2022, 27: 3129-3137. PMID: 35697759, PMCID: PMC9708554, DOI: 10.1038/s41380-022-01635-2.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus Statements
2021
Functional connectivity during frustration: a preliminary study of predictive modeling of irritability in youth
Scheinost D, Dadashkarimi J, Finn ES, Wambach CG, MacGillivray C, Roule AL, Niendam TA, Pine DS, Brotman MA, Leibenluft E, Tseng WL. Functional connectivity during frustration: a preliminary study of predictive modeling of irritability in youth. Neuropsychopharmacology 2021, 46: 1300-1306. PMID: 33479511, PMCID: PMC8134471, DOI: 10.1038/s41386-020-00954-8.Peer-Reviewed Original ResearchConceptsFunctional connectivityAttention-deficit/hyperactivity disorderCognitive flexibility taskDisruptive mood dysregulation disorderAffective Reactivity IndexLevels of irritabilityPreliminary fMRI studyCognitive flexibilityFlexibility taskIndividual differencesTransdiagnostic sampleFrontal networkFMRI studyHyperactivity disorderTask difficultyNeural mechanismsParent reportAnxiety symptomsSalience networkAnxiety disordersFrustrative nonrewardDimensional measuresPreliminary evidenceReactivity indexChild psychiatry
2020
Transdiagnostic, Connectome-Based Prediction of Memory Constructs Across Psychiatric Disorders
Barron DS, Gao S, Dadashkarimi J, Greene AS, Spann MN, Noble S, Lake EMR, Krystal JH, Constable RT, Scheinost D. Transdiagnostic, Connectome-Based Prediction of Memory Constructs Across Psychiatric Disorders. Cerebral Cortex 2020, 31: 2523-2533. PMID: 33345271, PMCID: PMC8023861, DOI: 10.1093/cercor/bhaa371.Peer-Reviewed Original ResearchConceptsMacroscale brain networksIndividual differencesBrain networksMemory deficitsFunctional connectivityAttention deficit hyper-activity disorderTask-based functional MRI dataLong-term memoryWhole-brain functional connectivityDiagnostic groupsWhole-brain patternsDefault mode networkFunctional MRI dataHuman Connectome ProjectPsychiatric disordersMemory constructsMemory performanceTransdiagnostic sampleBrain correlatesMode networkFunctional connectomeConnectome ProjectLimbic networkHealthy participantsMemoryA hitchhiker’s guide to working with large, open-source neuroimaging datasets
Horien C, Noble S, Greene AS, Lee K, Barron DS, Gao S, O’Connor D, Salehi M, Dadashkarimi J, Shen X, Lake EMR, Constable RT, Scheinost D. A hitchhiker’s guide to working with large, open-source neuroimaging datasets. Nature Human Behaviour 2020, 5: 185-193. PMID: 33288916, PMCID: PMC7992920, DOI: 10.1038/s41562-020-01005-4.Peer-Reviewed Original Research