2025
Identification and external validation of a problem cannabis risk network
Lichenstein S, Kiluk B, Potenza M, Garavan H, Chaarani B, Banaschewski T, Bokde A, Desrivières S, Flor H, Grigis A, Gowland P, Heinz A, Brühl R, Martinot J, Paillère Martinot M, Artiges E, Nees F, Orfanos D, Poustka L, Hohmann S, Holz N, Baeuchl C, Smolka M, Vaidya N, Walter H, Whelan R, Schumann G, Pearlson G, Yip S. Identification and external validation of a problem cannabis risk network. Biological Psychiatry 2025 PMID: 39909136, DOI: 10.1016/j.biopsych.2025.01.022.Peer-Reviewed Original ResearchAlcohol use outcomesCannabis useNeural mechanismsSample of treatment-seeking adultsNeural mechanisms of riskTreatment-seeking adultsCannabis use disorderNon-clinical sampleMechanisms of riskFunctional connectivity dataSample of adolescentsTreatment outcomesAssociated with harmful outcomesPoor treatment outcomesAddiction severityUse disorderEmerging adulthoodWhole-brainCannabisCollege studentsBrain developmentConnectivity dataIdentified networksTreatment approachesAdultsNeurobiological fingerprints of negative symptoms in schizophrenia identified by connectome‐based modeling
Gao Z, Xiao Y, Zhu F, Tao B, Zhao Q, Yu W, Bishop J, Gong Q, Lui S. Neurobiological fingerprints of negative symptoms in schizophrenia identified by connectome‐based modeling. Psychiatry And Clinical Neurosciences 2025, 79: 108-116. PMID: 39815736, DOI: 10.1111/pcn.13782.Peer-Reviewed Original ResearchConceptsConnectome-based predictive modelingNegative symptomsResting-state functional connectivity dataSeverity of negative symptomsDevelopment of novel treatment interventionsPrediction of negative symptomsDrug-naive schizophrenia patientsFirst-episode drug-naive schizophrenia patientsUnique neural substratesNovel treatment interventionsFunctional connectivity dataConnectome-based modelsSchizophrenia psychopathologySchizophrenia patientsNeurobiological mechanismsNeural substratesSymptom-specificSchizophreniaIndependent validation sampleError processNeural fingerprintsTreatment interventionsConnectivity patternsFunctional networksConnectivity data
2023
Transdiagnostic Connectome-Based Prediction of Craving
Garrison K, Sinha R, Potenza M, Gao S, Liang Q, Lacadie C, Scheinost D. Transdiagnostic Connectome-Based Prediction of Craving. American Journal Of Psychiatry 2023, 180: 445-453. PMID: 36987598, DOI: 10.1176/appi.ajp.21121207.Peer-Reviewed Original ResearchConceptsConnectome-based predictive modelingImagery conditionFunctional connectomeSelf-reported cravingStudy of motivationDefault mode networkFunctional connectivity dataIndependent samplesKey phenomenological featuresNeural signaturesTransdiagnostic sampleTransdiagnostic perspectiveMode networkMotivated behaviorCentral constructAddictive disordersHuman behaviorConnectivity dataPhenomenological featuresStrongest predictorCravingTaskSubstance use-related disordersConnectomeIndividuals
2022
Associations Between Early-Life Stress Exposure and Internalizing Symptomatology During the COVID-19 Pandemic: Assessing the Role of Neurobehavioral Mediators
Foster JC, Cohodes EM, Brieant AE, McCauley S, Odriozola P, Zacharek SJ, Pierre JC, Hodges HR, Kribakaran S, Haberman JT, Holt-Gosselin B, Gee DG. Associations Between Early-Life Stress Exposure and Internalizing Symptomatology During the COVID-19 Pandemic: Assessing the Role of Neurobehavioral Mediators. Biological Psychiatry Global Open Science 2022, 3: 362-373. PMID: 35959474, PMCID: PMC9356644, DOI: 10.1016/j.bpsgos.2022.07.006.Peer-Reviewed Original ResearchEarly life stressImpact of ELSResting-state functional connectivity dataEffects of ELSLife stress exposureCOVID-19 pandemicPandemic-related stressSignificant direct associationFunctional connectivity dataInternalizing symptomatologyELS exposurePsychiatric illnessOngoing COVID-19 pandemicGeneral populationSample of adultsPsychological functioningFunctional connectivityStress exposureMental healthSymptomatologyNeurobehavioral factorsAssociationEmotion regulationCOVIDDirect associationThreat imminence reveals links among unfolding of anticipatory physiological response, cortical-subcortical intrinsic functional connectivity, and anxiety
Abend R, Ruiz S, Bajaj M, Harrewijn A, Linke J, Atlas L, Winkler A, Pine D. Threat imminence reveals links among unfolding of anticipatory physiological response, cortical-subcortical intrinsic functional connectivity, and anxiety. Neurobiology Of Stress 2022, 16: 100428. PMID: 35036479, PMCID: PMC8749274, DOI: 10.1016/j.ynstr.2022.100428.Peer-Reviewed Original ResearchThreat imminenceAnticipatory physiological responsesAnxiety effectsPathological anxietyResting-state functional connectivity dataNon-painful thermal stimulationThreat-anticipation taskAnticipation of threatVentromedial prefrontal cortexIntrinsic functional connectivityFunctional connectivity dataDefensive responsesCortical-subcortical circuitsBasic neuroscience researchAnticipatory respondingPhysiological respondingDefensive respondingFear responsesMultivariate network analysisIntrinsic connectivityPrefrontal cortexAnxiety patientsNeuroscience researchPhysiological responsesFunctional connectivity
2021
Role of the cerebellum in the phenotype of neurodegenerative diseases: Mitigate or exacerbate?
Azizi S. Role of the cerebellum in the phenotype of neurodegenerative diseases: Mitigate or exacerbate? Neuroscience Letters 2021, 760: 136105. PMID: 34246702, DOI: 10.1016/j.neulet.2021.136105.Peer-Reviewed Original ResearchConceptsBehavioural component of emotionsFunctional connectivity dataComponents of emotionVisuospatial disordersFunctional connectivityBrain activityFMRI mapsBehavioral componentsCerebellar anatomyCerebellar vermisCerebellumConnectivity dataParkinson's patientsCerebral cortexCognitionIncreased activityBrainMotor-related inputsFMRIDegenerative diseasesSensory systemsCortexEmotionsNeuroscienceClinical symptomsEffects of Smoking Status and State on Intrinsic Connectivity
Yip SW, Lichenstein SD, Garrison K, Averill CL, Viswanath H, Salas R, Abdallah CG. Effects of Smoking Status and State on Intrinsic Connectivity. Biological Psychiatry Cognitive Neuroscience And Neuroimaging 2021, 7: 895-904. PMID: 33618016, PMCID: PMC8373998, DOI: 10.1016/j.bpsc.2021.02.004.Peer-Reviewed Original ResearchConceptsSmoking statusIntrinsic connectivityResting-state functional magnetic resonance imagingDefault mode connectivityIntrinsic connectivity distributionLong-term abstinenceFunctional magnetic resonance imagingMagnetic resonance imagingResting-state scanWhole-brain patternsControl nonsmokersSmoking reinstatementInterest-based analysisTobacco smokersFunctional connectivity dataTobacco abstinenceQuit attemptsOvernight abstinenceTobacco deprivationNovel treatmentsSmoking behaviorEarly abstinenceResonance imagingSalience networkFunctional connectivity
2020
Magnetic resonance image connectivity analysis provides evidence of central nervous system mode of action for parasacral transcutaneous electro neural stimulation - A pilot study
Netto JMB, Scheinost D, Onofrey JA, Franco I. Magnetic resonance image connectivity analysis provides evidence of central nervous system mode of action for parasacral transcutaneous electro neural stimulation - A pilot study. Journal Of Pediatric Urology 2020, 16: 536-542. PMID: 32873504, DOI: 10.1016/j.jpurol.2020.08.002.Peer-Reviewed Original ResearchConceptsDorsal lateral prefrontal cortexAnterior cingulate cortexOveractive bladderFunctional connectivityPrefrontal cortexUrinary tract symptomsSacral nerve stimulatorCommon treatment modalityRight scapular regionACC functional connectivityResting-state conditionsMechanism of actionTract symptomsMotor thresholdCentral effectsACC connectivityNerve stimulatorSacral levelTreatment modalitiesFunctional connectivity dataMechanism of effectivenessAdult volunteersFrontal lobeSubcortical regionsCingulate cortex
2019
Chapter 4 The uniqueness of the individual functional connectome
Horien C, Scheinost D, Constable R. Chapter 4 The uniqueness of the individual functional connectome. 2019, 63-81. DOI: 10.1016/b978-0-12-813838-0.00004-2.Peer-Reviewed Original ResearchFunctional magnetic resonance imagingIndividual differencesIndividual functional connectomesBrain functionConnectivity dataGroup-level differencesFunctional connectivity dataHuman neuroimagingBehavioral measuresFunctional connectomeMagnetic resonance imagingResonance imagingInterindividual heterogeneityNext turnConnectomeCognitionBest predictive modelNeuroimagingDifferencesParticipantsDisease
2018
Combining Multiple Connectomes via Canonical Correlation Analysis Improves Predictive Models
Gao S, Greene A, Todd Constable R, Scheinost D. Combining Multiple Connectomes via Canonical Correlation Analysis Improves Predictive Models. Lecture Notes In Computer Science 2018, 11072: 349-356. DOI: 10.1007/978-3-030-00931-1_40.Peer-Reviewed Original ResearchTask conditionsDifferent cognitive tasksMultiple task conditionsDifferent task conditionsConnectivity dataDifferent cognitive conditionsFunctional connectivity dataComputational modelHuman Connectome ProjectPrediction of behaviorCognitive tasksIndividual differencesBehavioral measuresBehavioral predictionsCognitive conditionsMultiple connectomesSingle taskFunctional connectivityConnectome ProjectDifferent tasksComplementary informationMultiple tasksTaskPrincipled methodCanonical correlation analysisMethylation in OTX2 and related genes, maltreatment, and depression in children
Kaufman J, Wymbs NF, Montalvo-Ortiz JL, Orr C, Albaugh MD, Althoff R, O’Loughlin K, Holbrook H, Garavan H, Kearney C, Yang BZ, Zhao H, Peña C, Nestler EJ, Lee RS, Mostofsky S, Gelernter J, Hudziak J. Methylation in OTX2 and related genes, maltreatment, and depression in children. Neuropsychopharmacology 2018, 43: 2204-2211. PMID: 30089883, PMCID: PMC6135753, DOI: 10.1038/s41386-018-0157-y.Peer-Reviewed Original ResearchConceptsMouse modelStress-related depressive disordersResting-state functional connectivity dataResting-state functional MRI dataDepressive-like behaviorEarly life stressSubset of childrenDNA specimensMedial frontal cortexPeripheral markersMeasures of depressionHomeobox 2 geneSubcallosal gyrusFunctional connectivity dataDepressive disorderFrontal cortexChild adversityMultiple molecular toolsFunctional MRI dataFrontal poleLarger studyFunctional connectivitySaliva samplesBilateral regionsUnbiased transcriptomics79. Transdiagnostic Prediction of Memory and Cognitive Abilities From Functional Connectivity Data: A Multidimensional Connectome-Based Predictive Modeling Study
Scheinost D, Gao S, Greene A, Constable R. 79. Transdiagnostic Prediction of Memory and Cognitive Abilities From Functional Connectivity Data: A Multidimensional Connectome-Based Predictive Modeling Study. Biological Psychiatry 2018, 83: s33. DOI: 10.1016/j.biopsych.2018.02.096.Peer-Reviewed Original ResearchFunctional connectivity dataCognitive abilitiesConnectivity dataPredictive modeling studiesMemoryConnectomeAbilityTask Integration for Connectome-Based Prediction Via Canonical Correlation Analysis
Gao S, Greene A, Constable R, Scheinost D. Task Integration for Connectome-Based Prediction Via Canonical Correlation Analysis. 2018, 87-91. DOI: 10.1109/isbi.2018.8363529.Peer-Reviewed Original ResearchTask conditionsDifferent tasksDifferent cognitive tasksMultiple task conditionsDifferent task conditionsConnectivity dataDifferent cognitive conditionsFunctional connectivity dataHuman Connectome ProjectComputational modelPrediction of behaviorCognitive tasksFluid intelligenceIndividual differencesBehavioral measuresBehavioral predictionsCognitive conditionsSingle taskFunctional connectivityConnectome ProjectComplementary informationTask integrationTaskProof of conceptCanonical correlation analysis
2017
An exemplar-based approach to individualized parcellation reveals the need for sex specific functional networks
Salehi M, Karbasi A, Shen X, Scheinost D, Constable RT. An exemplar-based approach to individualized parcellation reveals the need for sex specific functional networks. NeuroImage 2017, 170: 54-67. PMID: 28882628, PMCID: PMC5905726, DOI: 10.1016/j.neuroimage.2017.08.068.Peer-Reviewed Original ResearchConceptsIndividualized parcellationParcellation techniqueFunctional networksCross-validated predictive modelSpecific functional networksCerebral cortexPatient subgroupsFunctional connectivity dataFunctional organizationBrainParcellation schemesClinical applicationParcellation approachParcellationSexSubgroupsConnectivity dataIndividualized studyNetwork organizationIndividualsAmple evidencePatientsCortex
2013
Global Resting-State Functional Magnetic Resonance Imaging Analysis Identifies Frontal Cortex, Striatal, and Cerebellar Dysconnectivity in Obsessive-Compulsive Disorder
Anticevic A, Hu S, Zhang S, Savic A, Billingslea E, Wasylink S, Repovs G, Cole MW, Bednarski S, Krystal JH, Bloch MH, Li CS, Pittenger C. Global Resting-State Functional Magnetic Resonance Imaging Analysis Identifies Frontal Cortex, Striatal, and Cerebellar Dysconnectivity in Obsessive-Compulsive Disorder. Biological Psychiatry 2013, 75: 595-605. PMID: 24314349, PMCID: PMC3969771, DOI: 10.1016/j.biopsych.2013.10.021.Peer-Reviewed Original ResearchConceptsObsessive-compulsive disorderPrefrontal cortexResting-state functional connectivity dataStriatum/nucleus accumbensVentral striatum/nucleus accumbensResting-state functional connectivity studiesVentral anterior cingulate cortexCortico-striatal circuitsMagnetic Resonance Imaging AnalysisAnterior cingulate cortexFunctional connectivity studiesBasal gangliaControl subjectsFunctional connectivity dataAnterior thalamusRight putamenFrontal cortexNucleus accumbensDorsal striatumCerebellar cortexAbnormal neural connectivityCerebellar dysconnectivityCingulate cortexWhole brainFunctional magnetic resonance imaging (fMRI) analysis
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