2025
Static 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 conditions
2024
Findings of PTSD-specific deficits in default mode network strength following a mild experimental stressor
Averill C, Averill L, Akiki T, Fouda S, Krystal J, Abdallah C. Findings of PTSD-specific deficits in default mode network strength following a mild experimental stressor. NPP—Digital Psychiatry And Neuroscience 2024, 2: 9. PMID: 38919723, PMCID: PMC11197271, DOI: 10.1038/s44277-024-00011-y.Peer-Reviewed Original ResearchPosttraumatic stress disorderMajor depressive disorderConnectivity deficitsConnection strengthPrimary diagnosis of posttraumatic stress disorderExperimental stressorsDiagnosis of posttraumatic stress disorderResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingVentromedial prefrontal cortexDMN connectivity strengthStress-induced reductionEffect of groupDMN alterationsPrefrontal cortexDepressive disorderDMN connectivityStressor taskStress disorderBrain region(sAcute stressorFunctional connectivityDMNExploratory analysisDeficitsVoxel-based texture similarity networks reveal individual variability and correlate with biological ontologies
Lin L, Chang Z, Zhang Y, Xue K, Xie Y, Wei L, Li X, Zhao Z, Luo Y, Dong H, Liang M, Liu H, Yu C, Qin W, Ding H. Voxel-based texture similarity networks reveal individual variability and correlate with biological ontologies. NeuroImage 2024, 297: 120688. PMID: 38878916, DOI: 10.1016/j.neuroimage.2024.120688.Peer-Reviewed Original ResearchConceptsTest-retest reliabilityCovariance networksSouthwest University Adult Lifespan DatasetStructural magnetic resonance imagingStructural covariance networksStructural covariance patternsDorsal neocortexIndividual variabilitySimilarity networkHuman Connectome ProjectBrain regionsBrain processesBehavioral varianceLifespan datasetsSex differencesBiological substratesConnection strengthConnectome ProjectTopological propertiesCovariance patternsHuman brainNetwork topological propertiesIndividual structural covariance networksMagnetic resonance imagingNeocortexDistribution 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
2023
Tau-PET abnormality as a biomarker for Alzheimer’s disease staging and early detection: a topological perspective
Ding J, Shen C, Wang Z, Yang Y, Fakhri G, Lu J, Liang D, Zheng H, Zhou Y, Sun T, Study F. Tau-PET abnormality as a biomarker for Alzheimer’s disease staging and early detection: a topological perspective. Cerebral Cortex 2023, 33: 10649-10659. PMID: 37653600, DOI: 10.1093/cercor/bhad312.Peer-Reviewed Original ResearchConceptsStandardized uptake value ratioMild cognitive impairmentBrain regionsCognitive impairmentPositron emission tomographyMedial temporal lobeAlzheimer's diseaseVisual-related regionsTopological perspectiveTau positron emission tomographyMode networkTau PET imagingTopological featuresIndependent data cohortsTemporal lobeConnection strengthExtract topological featuresTau networksAbnormal networkProgression of Alzheimer's diseaseAbnormal protein accumulation
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