2025
Neuro- and social-cognition in schizotypal personality disorder and schizophrenia: A spectrum of severity
Goldstein K, Pietrzak R, Aladin S, Ng S, Chan C, Perez-Rodriguez M, Shafritz K, Kahn R, McClure M, Szeszko P, Hazlett E. Neuro- and social-cognition in schizotypal personality disorder and schizophrenia: A spectrum of severity. Psychiatry Research 2025, 348: 116445. PMID: 40117765, DOI: 10.1016/j.psychres.2025.116445.Peer-Reviewed Original ResearchSchizotypal personality disorderSocial cognitionPersonality disorderNegative symptomsNeuro-cognitiveSchizotypal personality disorder patientsCognitive impairmentCompared social cognitionSocial cognitive impairmentsSocial cognitive treatmentGeneral cognitive impairmentSocial-emotional cognitionGlobal cognitive impairmentProfile of clinical symptomsAssociated with greater reductionsCombined patient groupGender-matched healthy controlsNine-month follow-upSchizophrenia spectrumSchizophrenia patientsSchizophreniaDiagnostic groupsChange-over-timeCognitionGreater reductionsCELECOXIB ADDED TO RISPERIDONE FOR DEPRESSIVE SYMPTOMS IN FIRST-EPISODE AND DRUG NAÏ VE SCHIZOPHRENIA: PHARMACOGENETIC IMPACT OF BDNF GENE POLYMORPHISMS
Wang *, Chen X, Tian Y, Yu Z, Chen D, Xiu M, Kosten T, Zhang X. CELECOXIB ADDED TO RISPERIDONE FOR DEPRESSIVE SYMPTOMS IN FIRST-EPISODE AND DRUG NAÏ VE SCHIZOPHRENIA: PHARMACOGENETIC IMPACT OF BDNF GENE POLYMORPHISMS. The International Journal Of Neuropsychopharmacology 2025, 28: i158-i159. PMCID: PMC11815116, DOI: 10.1093/ijnp/pyae059.274.Peer-Reviewed Original ResearchHamilton Depression Rating ScaleBrain-derived neurotrophic factorPositive and Negative Syndrome ScaleBrain-derived neurotrophic factor serum levelsBrain-derived neurotrophic factor levelsSchizophrenia patientsTreatment of depressionDepressive symptomsPositive symptomsFirst-episodeSCZ patientsHamilton Depression Rating Scale total scoreBrain-derived neurotrophic factor systemComorbid major depressive disorderTreatment response to antidepressantsTotal scoreEarly stages of schizophreniaBrain-derived neurotrophic factor polymorphismsBrain-derived neurotrophic factor genotypePathogenesis of depressive symptomsBrain-derived neurotrophic factor gene polymorphismImprove treatment of depressionBrain-derived neurotrophic factor signalingHealthy controlsAmerican Journal of PsychiatryStatic and Dynamic Cross‐Network Functional Connectivity Shows Elevated Entropy in Schizophrenia Patients
Maksymchuk N, Miller R, Bustillo J, Ford J, Mathalon D, Preda A, Pearlson G, Calhoun V. Static and Dynamic Cross‐Network Functional Connectivity Shows Elevated Entropy in Schizophrenia Patients. Human Brain Mapping 2025, 46: e70134. PMID: 39924889, PMCID: PMC11808047, DOI: 10.1002/hbm.70134.Peer-Reviewed Original ResearchConceptsSZ patientsCognitive controlBrain networksFunctional connectivityHealthy controlsBrain domainsConnection strengthAnalyzed fMRI dataFunctional brain networksDiagnosed mental health conditionDynamic functional connectivityMental health conditionsSchizophrenia patientsSchizophreniaFMRI dataBrain statesEntropy correlationBrainDiseased brain statesSensorimotorControl groupK-means cluster analysisDMNConnection levelHealth conditionsNeurophysiological Markers of Auditory Verbal Hallucinations in Patients with Schizophrenia: An EEG Microstates Study
Li S, Hu R, Yan H, Chu L, Qiu Y, Gao Y, Li M, Li J. Neurophysiological Markers of Auditory Verbal Hallucinations in Patients with Schizophrenia: An EEG Microstates Study. Brain Topography 2025, 38: 29. PMID: 39920494, DOI: 10.1007/s10548-025-01105-2.Peer-Reviewed Original ResearchConceptsAVH patientsAuditory verbal hallucinationsSchizophrenia patientsNon-AVH groupHallucinating patientsMicrostate BEEG microstatesNeurophysiological markersPotential neurophysiological markersMicrostate CSeverity of symptomsVerbal hallucinationsPatientsHigh-density electroencephalography dataTherapeutic interventionsSchizophreniaClass C microstatesSeverityDurationNegative correlationGroupHallucinationsSymptomsGamma oscillations and excitation/inhibition imbalance: parallel effects of N-methyl D-aspartate receptor antagonism and psychosis
Roach B, Ford J, Nicholas S, Ferri J, Gunduz-Bruce H, Krystal J, Jaeger J, Mathalon D. Gamma oscillations and excitation/inhibition imbalance: parallel effects of N-methyl D-aspartate receptor antagonism and psychosis. Biological Psychiatry Cognitive Neuroscience And Neuroimaging 2025 PMID: 39832734, DOI: 10.1016/j.bpsc.2025.01.008.Peer-Reviewed Original ResearchN-methyl-D-aspartate glutamate receptorAuditory steady-state responsePhase-locking factorBroadband gamma powerGamma powerNMDAR hypofunctionAcute administration of ketamineN-methyl-D-aspartate glutamate receptor antagonistEvoked powerN-methyl-D-aspartate receptor antagonismDrug challenge studiesReplicate previous findingsReplicate prior studiesAdministration of ketamineHealthy control subjectsComparison of patientsSchizophrenia patientsAcute administrationSchizophreniaExcitation/inhibition imbalanceStudy 1Study 2Gamma oscillationsReceptor antagonismEEG studiesNeurobiological 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
2024
A Method for Multimodal IVA Fusion Within a MISA Unified Model Reveals Markers of Age, Sex, Cognition, and Schizophrenia in Large Neuroimaging Studies
Silva R, Damaraju E, Li X, Kochunov P, Ford J, Mathalon D, Turner J, van Erp T, Adali T, Calhoun V. A Method for Multimodal IVA Fusion Within a MISA Unified Model Reveals Markers of Age, Sex, Cognition, and Schizophrenia in Large Neuroimaging Studies. Human Brain Mapping 2024, 45: e70037. PMID: 39560198, PMCID: PMC11574741, DOI: 10.1002/hbm.70037.Peer-Reviewed Original ResearchConceptsMultimodal neuroimaging datasetSchizophrenia patientsNeuroimaging studiesCognitive performanceGroup differencesSchizophreniaSex effectsNeuroimaging datasetsMagnetic resonance imagingCognitionAge-associated declineControl subjectsMarkers of agingResonance imagingNon-imaging variablesSubject profilesSexNeuroimagingUK Biobank datasetPlasma NGAL, not IFN-γ, predicts early treatment response in drug-naïve Chinese Han schizophrenia patients
Sun X, Li M, Qiu Y, Su Q, Wang J, Bi F, Li J. Plasma NGAL, not IFN-γ, predicts early treatment response in drug-naïve Chinese Han schizophrenia patients. Schizophrenia Research 2024, 274: 457-463. PMID: 39515255, DOI: 10.1016/j.schres.2024.10.025.Peer-Reviewed Original ResearchDrug-naive schizophrenia patientsSchizophrenia patientsNeutrophil gelatinase-associated lipocalinNeutrophil gelatinase-associated lipocalin concentrationsEarly treatment responseDuration of untreated illnessTreatment responseIFN-gHealthy controlsNGAL concentrationsEarly prediction of treatment efficacyPlasma neutrophil gelatinase-associated lipocalinNeutrophil gelatinase-associated lipocalin levelsUntreated illnessPrediction of treatment efficacyPredicting early treatment responsePlasma NGAL concentrationsWeeks of treatmentIFN-g levelsPersonalized treatment strategiesLogistic regression analysisBaseline NGAL concentrationLongitudinal studySchizophreniaTreatment outcomesFusion of Novel FMRI Features Using Independent Vector Analysis for a Multifaceted Characterization of Schizophrenia
Jia C, Abu Baker Siddique Akhonda M, Yang H, Calhoun V, Adali T. Fusion of Novel FMRI Features Using Independent Vector Analysis for a Multifaceted Characterization of Schizophrenia. 2015 23rd European Signal Processing Conference (EUSIPCO) 2024, 1112-1116. DOI: 10.23919/eusipco63174.2024.10715096.Peer-Reviewed Original ResearchFractional amplitude of low-frequency fluctuationAmplitude of low-frequency fluctuationResting-state functional magnetic resonanceCharacterization of schizophreniaFunctional magnetic resonanceBrain activity changesLow-frequency fluctuationsVisual cortexSchizophrenia patientsSchizophrenia NetworkBrain alterationsPsychiatric conditionsBrain regionsSchizophrenia biomarkersSchizophreniaFMRI featuresFractional amplitudeGroup differencesFMRI dataNeuroimaging analysisIndependent vector analysisActivity changesHealthy controlsBrainHigher-order statistical informationComparative Analysis of Fecal Microbiota Between Adolescents with Early-Onset Psychosis and Adults with Schizophrenia
Nuncio-Mora L, Nicolini H, Lanzagorta N, García-Jaimes C, Sosa-Hernández F, González-Covarrubias V, Cabello-Rangel H, Sarmiento E, Glahn D, Genis-Mendoza A. Comparative Analysis of Fecal Microbiota Between Adolescents with Early-Onset Psychosis and Adults with Schizophrenia. Microorganisms 2024, 12: 2071. PMID: 39458380, PMCID: PMC11510430, DOI: 10.3390/microorganisms12102071.Peer-Reviewed Original ResearchEarly-onset psychosisPsychiatric disordersAtypical antipsychotic treatmentNon-psychotic individualsTreated with sertralineAntipsychotic treatmentSchizophrenia groupSchizophrenia patientsSchizophreniaGut-brain axisPsychosisGene orthology analysisPotential metabolic functionsAssociated with gut dysbiosisFunctional prediction analysisValproate treatmentPharmacological treatmentOscillospiraceae familiesOrthology analysisDecreased levelsFatty acid metabolismGut microbiomeExpressed genesMicrobial communitiesMicrobial compositionMultilayer network analysis reveals instability of brain dynamics in untreated first-episode schizophrenia
Gao Z, Xiao Y, Zhu F, Tao B, Zhao Q, Yu W, Sweeney J, Gong Q, Lui S. Multilayer network analysis reveals instability of brain dynamics in untreated first-episode schizophrenia. Cerebral Cortex 2024, 34: bhae402. PMID: 39375878, DOI: 10.1093/cercor/bhae402.Peer-Reviewed Original ResearchConceptsDorsal attention networkFirst-episode schizophreniaNetwork switching rateAntipsychotic treatmentSchizophrenia patientsReduction of negative symptomsResting-state functional magnetic resonance imaging dataUntreated first-episode schizophreniaDrug-naive schizophrenia patientsHealthy controlsFunctional magnetic resonance imaging dataEarly-stage schizophreniaFirst-episode drug-naive schizophrenia patientsInferior parietal lobuleFunctional network activityBrain network activityMagnetic resonance imaging dataNetwork activityAntipsychotic medicationNegative symptomsParietal lobuleAcute psychosisParietal regionsSchizophreniaMultilayer network analysisApplications of MRI in Schizophrenia: Current Progress in Establishing Clinical Utility
Sun H, Liu N, Qiu C, Tao B, Yang C, Tang B, Li H, Zhan K, Cai C, Zhang W, Lui S. Applications of MRI in Schizophrenia: Current Progress in Establishing Clinical Utility. Journal Of Magnetic Resonance Imaging 2024, 61: 616-633. PMID: 38946400, DOI: 10.1002/jmri.29470.Peer-Reviewed Original ResearchMagnetic resonance imagingTreatment outcome of schizophreniaOutcome of schizophreniaSevere mental illnessSchizophrenia patientsSchizophreniaIllness onsetPredicting symptomsBrain abnormalitiesClinical utilityMental illnessTreatment outcomesDecades of researchFindings of magnetic resonance imagingScreening high-risk individualsLife of affected individualsHigh-risk individualsPromote clinical translationResonance imagingIncreased mortality rateResponse processApplication of magnetic resonance imagingSymptomsPrognostic toolResearch findingsGray matters: ViT-GAN framework for identifying schizophrenia biomarkers linking structural MRI and functional network connectivity
Bi Y, Abrol A, Jia S, Sui J, Calhoun V. Gray matters: ViT-GAN framework for identifying schizophrenia biomarkers linking structural MRI and functional network connectivity. NeuroImage 2024, 297: 120674. PMID: 38851549, DOI: 10.1016/j.neuroimage.2024.120674.Peer-Reviewed Original ResearchFunctional network connectivityMedial prefrontal cortexBrain structuresFunctional network connectivity matricesPrefrontal cortexStructural MRINetwork connectivityGray matterSelf-attention mechanismGenerative adversarial networkDeep learning architectureBrain disordersDorsolateral prefrontal cortexResearch of schizophreniaNeural signal processingIdentified functional connectivityCross-domain analysisAttention mapsStructural biomarkersAdversarial networkLearning architectureDL-PFCICA algorithmSchizophrenia patientsHigh-dimensional fMRI dataAbnormal regional homogeneity as a potential imaging indicator for identifying adolescent-onset schizophrenia: Insights from resting-state functional magnetic resonance imaging
Zhou Y, Zhu H, Hu W, Song Y, Zhang S, Peng Y, Yang G, Shi H, Yang Y, Li W, Lv L, Zhang Y. Abnormal regional homogeneity as a potential imaging indicator for identifying adolescent-onset schizophrenia: Insights from resting-state functional magnetic resonance imaging. Asian Journal Of Psychiatry 2024, 98: 104106. PMID: 38865883, DOI: 10.1016/j.ajp.2024.104106.Peer-Reviewed Original ResearchAdolescent-onset schizophreniaReHo valuesRegional homogeneityAdolescent-onset schizophrenia patientsResting-state functional magnetic resonance imaging scansFunctional magnetic resonance imaging scansRight middle frontal gyrusResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingEducation-matched controlsMiddle frontal gyrusLeft precentral gyrusAbnormal regional homogeneityAO patientsFunctional magnetic resonanceLeft inferior parietalPANSS scoresMagnetic resonance imaging scansSchizophrenia patientsFrontal gyrusAngular gyriReHo abnormalitiesInferior parietalPrecentral gyrusReHo methodA confounder controlled machine learning approach: Group analysis and classification of schizophrenia and Alzheimer’s disease using resting-state functional network connectivity
Hassanzadeh R, Abrol A, Pearlson G, Turner J, Calhoun V. A confounder controlled machine learning approach: Group analysis and classification of schizophrenia and Alzheimer’s disease using resting-state functional network connectivity. PLOS ONE 2024, 19: e0293053. PMID: 38768123, PMCID: PMC11104643, DOI: 10.1371/journal.pone.0293053.Peer-Reviewed Original ResearchConceptsResting-state functional network connectivityFunctional network connectivityResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingAlzheimer's diseaseClassification of schizophreniaNetwork pairsPatients to healthy controlsSchizophrenia patientsNeurobiological mechanismsSZ patientsSubcortical networksCerebellum networkSchizophreniaRs-fMRIDisorder developmentMotor networkCompare patient groupsSubcortical domainSZ disorderHealthy controlsMagnetic resonance imagingDisordersNetwork connectivityFunctional abnormalitiesLongitudinal Data Analysis
Diggle P, Taylor-Robinson D. Longitudinal Data Analysis. 2024, 1-34. DOI: 10.1007/978-1-4614-6625-3_75-1.Peer-Reviewed Original ResearchTime-to-event outcomesBinary responsesTreatment of missing valuesClinical trials of drug therapyJoint modelTrials of drug therapyCystic fibrosis patientsLongitudinal studyLinear modelCross-sectional studySchizophrenia patientsFibrosis patientsLong-term progressionDrug therapyClinical trialsLung functionObservational studyNon-independencePatientsOutcome variablesStatistical methodsImmunosenescence-related T cell phenotypes and white matter in schizophrenia patients with tardive dyskinesia
Li N, Li Y, Yu T, Gou M, Chen W, Wang X, Tong J, Chen S, Tan S, Wang Z, Tian B, Li C, Tan Y. Immunosenescence-related T cell phenotypes and white matter in schizophrenia patients with tardive dyskinesia. Schizophrenia Research 2024, 269: 36-47. PMID: 38723519, DOI: 10.1016/j.schres.2024.04.017.Peer-Reviewed Original ResearchCD95+ T cellsTardive dyskinesiaT-cell phenotypeT cell subpopulationsBrain structural abnormalitiesT cellsSchizophrenia patientsFractional anisotropyCD95+Distribution of T cell phenotypesStructural abnormalitiesAssociated with brain structural abnormalitiesMemory T-cell subpopulationsCD8+ T cellsLevels of IFN-gInferior fronto-occipital fasciculusLevels of cytokinesSuperior longitudinal fasciculusFronto-occipital fasciculusChoroid plexus volumeIntracellular levelsWhite matter tractsOrofacial TDPallidum volumesPublished routinesMonozygotic twins discordant for schizophrenia differ in maturation and synaptic transmission
Stern S, Zhang L, Wang M, Wright R, Rosh I, Hussein Y, Stern T, Choudhary A, Tripathi U, Reed P, Sadis H, Nayak R, Shemen A, Agarwal K, Cordeiro D, Peles D, Hang Y, Mendes A, Baul T, Roth J, Coorapati S, Boks M, McCombie W, Hulshoff Pol H, Brennand K, Réthelyi J, Kahn R, Marchetto M, Gage F. Monozygotic twins discordant for schizophrenia differ in maturation and synaptic transmission. Molecular Psychiatry 2024, 29: 3208-3222. PMID: 38704507, PMCID: PMC11449799, DOI: 10.1038/s41380-024-02561-1.Peer-Reviewed Original ResearchCo-twinSchizophrenia patientsMonozygotic twinsHippocampal synaptic deficitsHealthy twinsSynapse-related genesDepressive disorderPsychiatric disordersSchizophreniaControl twinsTwin pairsSynaptic activitySynaptic deficitsTwin siblingsNeurophysiological abnormalitiesGroup of patientsSynaptic transmissionDiscordant twinsDisordersHippocampal neuronsNeuronsReprogrammed iPSCsIPSC modelsPatientsSiblingsSelective disrupted gray matter volume covariance of amygdala subregions in schizophrenia
Chang Z, Liu L, Lin L, Wang G, Zhang C, Tian H, Liu W, Wang L, Zhang B, Ren J, Zhang Y, Xie Y, Du X, Wei X, Wei L, Luo Y, Dong H, Li X, Zhao Z, Liang M, Zhang C, Wang X, Yu C, Qin W, Liu H. Selective disrupted gray matter volume covariance of amygdala subregions in schizophrenia. Frontiers In Psychiatry 2024, 15: 1349989. PMID: 38742128, PMCID: PMC11090100, DOI: 10.3389/fpsyt.2024.1349989.Peer-Reviewed Original ResearchGray matter volume covarianceGray matter volumeAnterior amygdaloid areaAmygdala subregionsSchizophrenia patientsNegative Symptom ScaleVoxel-wise general linear modelHealthy controlsDuration of illnessOrbitofrontal cortexMatter volumeRight BASchizophreniaAmygdalaSymptom ScaleConnectivity patternsSubregionsSample size of patientsSize of patientsFunctional abnormalitiesCorrelation analysisStriatumGeneralized linear modelPatientsHippocampusDistribution of Connectivity Strengths Across Functional Regions has Higher Entropy in Schizophrenia Patients than in Controls
Maksymchuk N, Miller R, Calhoun V. Distribution of Connectivity Strengths Across Functional Regions has Higher Entropy in Schizophrenia Patients than in Controls. 2024, 00: 37-40. DOI: 10.1109/ssiai59505.2024.10508663.Peer-Reviewed Original ResearchFunctional magnetic resonance imagingGroup independent component analysisSchizophrenia patientsCognitive controlResting-state functional magnetic resonance imagingIntrinsic connectivity networksHealthy controlsGender-matched healthy controlsSZ patientsNeuropsychiatric disordersBrain areasBrain networksSchizophreniaDisrupted integrityBrain domainsConnection strengthIndependent component analysisConnectivity networksMagnetic resonance imagingSomatomotorDistribution of connection strengthsResonance imagingCross-sectional dataPatientsDiagnostic tests
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