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 featuresBehaviorConceptualizationCommentaryStudyFindingsSubstancesNetwork state dynamics underpin basal craving in a transdiagnostic population
Ye J, Garrison K, Lacadie C, Potenza M, Sinha R, Goldfarb E, Scheinost D. Network state dynamics underpin basal craving in a transdiagnostic population. Molecular Psychiatry 2024, 1-10. PMID: 39183336, DOI: 10.1038/s41380-024-02708-0.Peer-Reviewed Original ResearchConnectome-based predictive modelingBrain responsesRegulation of affective statesSample of healthy controlsTransdiagnostic populationTransdiagnostic sampleHigher cravingMotivational stateCravingFMRI methodsAffective statesScan runsExperimental stimuliNetwork engagementBrain dynamicsClinical implicationsHealthy controlsBrainIndividual variationState dynamicsCharacterize individualsReplication datasetPsychopathologyFMRIEngagement
2023
Distinct neural networks predict cocaine versus cannabis treatment outcomes
Lichenstein S, Kohler R, Ye F, Potenza M, Kiluk B, Yip S. Distinct neural networks predict cocaine versus cannabis treatment outcomes. Molecular Psychiatry 2023, 28: 3365-3372. PMID: 37308679, PMCID: PMC10713861, DOI: 10.1038/s41380-023-02120-0.Peer-Reviewed Original ResearchConceptsConnectome-based predictive modelingCognitive behavior therapyCognitive behavioral therapySubstance use disordersCannabis abstinenceNeural mechanismsBehavior therapyDistinct neural networksComputer-based trainingCannabis use disorderFMRI scanningNeural predictorsStudy 1Study 2Treatment outcomesContingency managementPrior workComparison subjectsNetwork strengthUse disordersNovel treatment targetsAbstinenceIndependent samplesCocaine abstinenceTreatment respondersTransdiagnostic 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