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 responders
2022
Current Substance Use and Maternal Neural Responses to Infant Faces and Cries
Wall K, Dell J, Lowell A, Potenza M, Mayes L, Rutherford H. Current Substance Use and Maternal Neural Responses to Infant Faces and Cries. International Journal Of Mental Health And Addiction 2022, 22: 1629-1644. DOI: 10.1007/s11469-022-00947-2.Peer-Reviewed Original ResearchInfant cuesCurrent substance useInfant facesSubstance useNeural responsesMaternal neural responseUnknown infant facesSubstance use effectsN170 responseChild developmentMaternal substance useSubstance use assessmentCuesLong delayContinuous measureElectroencephalographyCentral findingPrior workFaceSalienceHigh levelsCaregivingStimuliUse assessmentFamiliarityk-SALSA: k-Anonymous Synthetic Averaging of Retinal Images via Local Style Alignment
Jeon M, Park H, Kim H, Morley M, Cho H. k-SALSA: k-Anonymous Synthetic Averaging of Retinal Images via Local Style Alignment. Lecture Notes In Computer Science 2022, 13681: 661-678. PMID: 37525827, PMCID: PMC10388376, DOI: 10.1007/978-3-031-19803-8_39.Peer-Reviewed Original ResearchStyle alignmentMembership inference attacksRetinal imagesGenerative adversarial networkPotential of machineRetinal image analysisRetinal fundus imagesK-anonymityInference attacksPrivacy notionPrivate datasetAdversarial networkData sharingBenchmark datasetsTraining dataClassification performanceModern machineArt techniquesSource imagesImage fidelityFundus imagesPrior workVisual patternsImage analysisImagesIncremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation
You C, Xiang J, Su K, Zhang X, Dong S, Onofrey J, Staib L, Duncan J. Incremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation. Lecture Notes In Computer Science 2022, 13573: 3-16. PMID: 37415747, PMCID: PMC10323962, DOI: 10.1007/978-3-031-18523-6_1.Peer-Reviewed Original ResearchIncremental learningMedical image segmentation tasksMulti-site datasetImage segmentation tasksMedical image segmentationProstate MRI SegmentationComputation resourcesMedical datasetsSegmentation taskImage segmentationSegmentation frameworkEmbedding featuresBenchmark datasetsMRI segmentationTraining dataTarget domainLearning approachPractical deploymentDomain-specific expertiseCompetitive performanceDatasetTraining schemePrior workSegmentationSingle model
2021
Increased face detection responses on the mooney faces test in people at clinical high risk for psychosis
Silverstein SM, Thompson JL, Gold JM, Schiffman J, Waltz JA, Williams TF, Zinbarg RE, Mittal VA, Ellman LM, Strauss GP, Walker EF, Woods SW, Levin JA, Kafadar E, Kenney J, Smith D, Powers AR, Corlett PR. Increased face detection responses on the mooney faces test in people at clinical high risk for psychosis. Schizophrenia 2021, 7: 26. PMID: 34001909, PMCID: PMC8129098, DOI: 10.1038/s41537-021-00156-1.Peer-Reviewed Original ResearchClinical high riskFace perceptionCHR groupDegraded face imagesCognitive processesPerceptual sensitivityRisk mental stateMotivational mechanismsVisual perceptionFace testPerceptual abnormalitiesMental statesCHR participantsCHR subjectsMore facePerceptionDetection responseFace imagesYoung peoplePsychosisClinical measuresParticipantsPrior workFacePrior studies
2019
When is it Okay to be Alone? Gender Differences in Normative Beliefs about Social Withdrawal in Emerging Adulthood
Bowker J, Ooi L, Coplan R, Etkin R. When is it Okay to be Alone? Gender Differences in Normative Beliefs about Social Withdrawal in Emerging Adulthood. Sex Roles 2019, 82: 482-492. DOI: 10.1007/s11199-019-01065-5.Peer-Reviewed Original Research
2018
Atypical frontoamygdala functional connectivity in youth with autism
Odriozola P, Dajani DR, Burrows CA, Gabard-Durnam LJ, Goodman E, Baez AC, Tottenham N, Uddin LQ, Gee DG. Atypical frontoamygdala functional connectivity in youth with autism. Developmental Cognitive Neuroscience 2018, 37: 100603. PMID: 30581125, PMCID: PMC6570504, DOI: 10.1016/j.dcn.2018.12.001.Peer-Reviewed Original ResearchConceptsAutism spectrum disorderRostral anterior cingulate cortexFunctional connectivityTD individualsDifferent age-related patternsResting-state functional connectivityOverall group differencesBroad developmental rangeAnterior cingulate cortexSocioemotional functioningSocioemotional impairmentsSpectrum disorderCross-sectional sampleAge-related changesRight basolateral amygdalaCingulate cortexAge-related patternsGroup differencesDevelopmental rangeFrontoamygdala circuitryBasolateral amygdalaAmygdalaIndividualsPrior workImpairmentTraining in cognitive strategies reduces eating and improves food choice
Boswell RG, Sun W, Suzuki S, Kober H. Training in cognitive strategies reduces eating and improves food choice. Proceedings Of The National Academy Of Sciences Of The United States Of America 2018, 115: e11238-e11247. PMID: 30420496, PMCID: PMC6275472, DOI: 10.1073/pnas.1717092115.Peer-Reviewed Original ResearchConceptsCognitive strategiesFood valuationBrief trainingUnhealthy foodsCognitive regulation strategiesFood choicesEffects of framingRegulation strategiesStudy 5Study 1Study 3Unhealthy eatingStudy 6Training componentHealthy food choicesNegative consequencesPositive benefitsCravingHealthy foodsTrainingClinical implicationsPrior workIndividualsImplicationsEatingBayesian adaptive algorithms for locating HIV mobile testing services
Gonsalves GS, Copple JT, Johnson T, Paltiel AD, Warren JL. Bayesian adaptive algorithms for locating HIV mobile testing services. BMC Medicine 2018, 16: 155. PMID: 30173667, PMCID: PMC6120098, DOI: 10.1186/s12916-018-1129-0.Peer-Reviewed Original ResearchConceptsThompson SamplingSearch algorithmMobile testing serviceTesting activitiesSpatial correlationTesting resourcesAlgorithmBayesian adaptive algorithmPrior workHigh spatial correlationWeighting schemeAdaptive algorithmSearch strategySimulation modelPractical valueHierarchical modelServicesPerfect informationMobile HIV testing servicesInformationHIV testing resourcesCombining Phenotypic and Resting-State FMRI Data for Autism Classification with Recurrent Neural Networks
Dvornek NC, Ventola P, Duncan JS. Combining Phenotypic and Resting-State FMRI Data for Autism Classification with Recurrent Neural Networks. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2018, 2018: 725-728. PMID: 30288208, PMCID: PMC6166875, DOI: 10.1109/isbi.2018.8363676.Peer-Reviewed Original ResearchAutism spectrum disorderRecurrent neural networkNeural networkAutism Brain Imaging Data ExchangeSingle deep learning frameworkHeterogeneity of ASDFunctional magnetic resonance imagingDeep learning frameworkResting-state fMRI dataResting-state functional magnetic resonance imagingBetter classification accuracyAutism classificationSpectrum disorderData exchangeLearning frameworkFMRI dataClassification accuracyCross-validation frameworkChallenging taskStraightforward taskPrior workNetworkSuch dataRsfMRITask
2013
Stressful events and psychological difficulties: testing alternative candidates for sensitivity
Laceulle OM, O’Donnell K, Glover V, O’Connor T, Ormel J, van Aken MA, Nederhof E. Stressful events and psychological difficulties: testing alternative candidates for sensitivity. European Child & Adolescent Psychiatry 2013, 23: 103-113. PMID: 23756816, DOI: 10.1007/s00787-013-0436-4.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAffective SymptomsAnxiety DisordersChildChild DevelopmentChild of Impaired ParentsChild, PreschoolDisease SusceptibilityFemaleHumansLife Change EventsMaleMothersPregnancyPrenatal Exposure Delayed EffectsProspective StudiesRisk FactorsSex FactorsSocial EnvironmentSocioeconomic FactorsStress, PsychologicalSurveys and QuestionnairesTime FactorsConceptsPsychological difficultiesStressful eventsDifficult temperamentPrenatal anxietyLife eventsSources of sensitivityStressful life eventsPrenatal maternal anxietyChild developmentReciprocal associationsAge 7Maternal anxietyAge 4Child's ageTemperamentLongitudinal studyStress exposureAnxietyEarly childhoodCurrent studyConsistent evidenceChildrenPrior workDifficultiesAdditional research
2003
A model of risk for major depression: Effects of life stress and cognitive style vary by age
Mazure CM, Maciejewski PK. A model of risk for major depression: Effects of life stress and cognitive style vary by age. Depression And Anxiety 2003, 17: 26-33. PMID: 12577275, DOI: 10.1002/da.10081.Peer-Reviewed Original ResearchConceptsCognitive styleElderly adultsStable risk factorsStress-diathesis modelModel of riskAdverse life eventsAge-specific perspectiveMajor depressionLife eventsPersonal vulnerabilityLife stressEvent typesAge-specific approachesEvidence-based modelYoung adultsIndependent samplesRisk of depressionStyleDepressionHigh needAdultsPrior workEmpirical studySociotropyAdverse event types
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