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
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
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