A machine-learning approach for differentiating borderline personality disorder from community participants with brain-wide functional connectivity
Lahnakoski J, Nolte T, Solway A, Vilares I, Hula A, Feigenbaum J, Lohrenz T, King-Casas B, Fonagy P, Montague P, Schilbach L. A machine-learning approach for differentiating borderline personality disorder from community participants with brain-wide functional connectivity. Journal Of Affective Disorders 2024, 360: 345-353. PMID: 38806064, DOI: 10.1016/j.jad.2024.05.125.Peer-Reviewed Original ResearchBorderline personality disorderPrediction of borderline personality disorderFunctional connectivityPersonality disorderBorderline personality disorder patientsBorderline personality disorder statusBrain-wide functional connectivityBiomarkers of psychiatric disordersFunctional connectivity markersFunctional connectivity patternsSelf-reported resultsClinical interviewPsychiatric disordersSomatomotor regionsChance levelSeed ROIConnectivity markersComparison correctionSeed regionConnectivity patternsDiscrimination performanceConnectivity valuesDisordersBorderlineGeneralizabilityBayesian Decision-Making Under Uncertainty in Borderline Personality Disorder.
Manavalan M, Song X, Nolte T, Fonagy P, Montague P, Vilares I. Bayesian Decision-Making Under Uncertainty in Borderline Personality Disorder. Journal Of Personality Disorders 2024, 38: 53-74. PMID: 38324252, DOI: 10.1521/pedi.2024.38.1.53.Peer-Reviewed Original ResearchConceptsBorderline personality disorder patientsBorderline personality disorderPersonality disorderCharacteristics of borderline personality disorderSensorimotor tasksDomain-generalGeneral deficitPotential deficitsHealthy controlsDeficitsOptimal decision-makingDisordersTaskLowered levelsSensorimotorBorderlineCurrent informationDecision-makingBeliefsPerception