2024
Networks extracted from nonlinear fMRI connectivity exhibit unique spatial variation and enhanced sensitivity to differences between individuals with schizophrenia and controls
Kinsey S, Kazimierczak K, Camazón P, Chen J, Adali T, Kochunov P, Adhikari B, Ford J, van Erp T, Dhamala M, Calhoun V, Iraji A. Networks extracted from nonlinear fMRI connectivity exhibit unique spatial variation and enhanced sensitivity to differences between individuals with schizophrenia and controls. Nature Mental Health 2024, 2: 1464-1475. PMID: 39650801, PMCID: PMC11621020, DOI: 10.1038/s44220-024-00341-y.Peer-Reviewed Original ResearchSelf-referential cognitionFunctional magnetic resonance imaging connectivityFunctional brain connectivityCingulo-opercularDefault-modeSchizophrenia diagnosisExecutive regionsFMRI connectivityFunctional connectivityConnectivity analysisSchizophreniaSensitive to differencesBrain connectivityFunctional connectivity structureWidespread alterationsImaging connectivityIndependent component analysisBrain phenomenaNetwork integrationHypoconnectivityPsychosisCognitionCore regionNonlinear networksCase-control datasetA 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 datasetInterplay between preclinical indices of obesity and neural signatures of fluid intelligence in youth
Ward T, Schantell M, Dietz S, Ende G, Rice D, Coutant A, Arif Y, Wang Y, Calhoun V, Stephen J, Heinrichs-Graham E, Taylor B, Wilson T. Interplay between preclinical indices of obesity and neural signatures of fluid intelligence in youth. Communications Biology 2024, 7: 1285. PMID: 39379610, PMCID: PMC11461743, DOI: 10.1038/s42003-024-06924-w.Peer-Reviewed Original ResearchConceptsAbstract reasoning taskFluid intelligenceAbstract reasoningBrain regionsNeural activityReasoning tasksLeft dorsolateral prefrontal cortexLeft temporoparietal junctionDorsolateral prefrontal cortexHigher-order cognitionWhole-brain correlationHigh-density magnetoencephalographySignificant oscillatory responsesYouth aged 9Prefrontal cortexTemporoparietal junctionNeural signaturesTheta oscillationsResponse scaleWhole-brainNeurobehavioral functionNeural dynamicsAged 9CognitionReaction timeAssociations of alcohol and tobacco use with psychotic, depressive and developmental disorders revealed via multimodal neuroimaging
Qiu L, Liang C, Kochunov P, Hutchison K, Sui J, Jiang R, Zhi D, Vergara V, Yang X, Zhang D, Fu Z, Bustillo J, Qi S, Calhoun V. Associations of alcohol and tobacco use with psychotic, depressive and developmental disorders revealed via multimodal neuroimaging. Translational Psychiatry 2024, 14: 326. PMID: 39112461, PMCID: PMC11306356, DOI: 10.1038/s41398-024-03035-2.Peer-Reviewed Original ResearchConceptsFronto-limbic networkSalience networkAssociated with cognitionFronto-basal gangliaDevelopmental disordersBrain networksLimbic systemAlcohol useAssociated with alcohol useMultimodal brain networksTobacco useAssociation of alcoholPsychiatric disordersMultimodal neuroimagingDMNBrain featuresCognitionAlcohol/tobacco useDisordersAssociated with tobacco useDepressionSymptomsFunctional abnormalitiesAlcoholBrain4D dynamic spatial brain networks at rest linked to cognition show atypical variability and coupling in schizophrenia
Pusuluri K, Fu Z, Miller R, Pearlson G, Kochunov P, Van Erp T, Iraji A, Calhoun V. 4D dynamic spatial brain networks at rest linked to cognition show atypical variability and coupling in schizophrenia. Human Brain Mapping 2024, 45: e26773. PMID: 39045900, PMCID: PMC11267451, DOI: 10.1002/hbm.26773.Peer-Reviewed Original ResearchConceptsBrain networksFunctional magnetic resonance imagingAssociated with cognitive performanceDynamics of functional brain networksAssociated with cognitionFunctional brain networksVoxel-wise changesVolumetric couplingDynamical variablesCognitive performanceTypical controlsSchizophreniaCognitive impairmentNetwork pairsMagnetic resonance imagingPair of networksCognitionAtypical variabilityResonance imagingCouplingNetwork connectivityNetwork growthImpairmentBrainStatic networksA Method to Estimate Longitudinal Change Patterns in Functional Network Connectivity of the Developing Brain Relevant to Psychiatric Problems, Cognition, and Age
Saha R, Saha D, Rahaman A, Fu Z, Liu J, Calhoun V. A Method to Estimate Longitudinal Change Patterns in Functional Network Connectivity of the Developing Brain Relevant to Psychiatric Problems, Cognition, and Age. Brain Connectivity 2024, 14: 130-140. PMID: 38308475, PMCID: PMC10954605, DOI: 10.1089/brain.2023.0040.Peer-Reviewed Original ResearchFunctional network connectivityFunctional connectivityPsychiatric problemsFunctional network connectivity matricesNetwork connectivityMultivariate patternsWhole-brain functional networksIntrinsic functional connectivityPattern of functional changesBrain functional connectivityIntrinsic functional relationshipLongitudinal changesAdolescent brainAge-related changesBrain networksStudy developmental changesScanning sessionBrain functionAssociated with longitudinal changesCognitive scoresDevelopmental changesBrain developmentFunctional changesCognitionLongitudinal change patterns
2023
Resting‐state dynamic functional network connectivity predicts cognition in 37,784 participants of UK Biobank
Sendi M, Zendehrouh E, Miller R, Salat D, Calhoun V. Resting‐state dynamic functional network connectivity predicts cognition in 37,784 participants of UK Biobank. Alzheimer's & Dementia 2023, 19 DOI: 10.1002/alz.065832.Peer-Reviewed Original ResearchFunctional network connectivityDynamic FNCDynamic functional network connectivityCognitive scoresFluid intelligenceCognitive declineAge-related cognitive declineGroup independent component analysisResting-state functional MRIBrain functional changesResting-state fMRIBrain functional network connectivityReaction timeParticipants of UK BiobankRT taskFunctional MRIRs-fMRIPairing taskCognitionIndependent component analysisUK BiobankBrainNetwork connectivityHealthy adultsData-driven componentsFusion of Multi-Modal Neuroimaging Data and Association With Cognitive Data
LoPresto M, Akhonda M, Calhoun V, Adali T. Fusion of Multi-Modal Neuroimaging Data and Association With Cognitive Data. 2023, 00: 1-5. DOI: 10.1109/icasspw59220.2023.10193147.Peer-Reviewed Original ResearchHopkins Verbal Learning TestNeuropsychological assessment batteryCognitive dataNeuroimaging modalitiesBrief Assessment of CognitionSchizophrenia composite scoreVerbal Learning TestAssessment of CognitionMultiple neuroimaging modalitiesBrief AssessmentCross-modal connectionsLearning TestAssessment batteryCross-modal relationshipsNeuroimaging dataBrain benefitsCognitive scoresComposite scoreCognitionData-driven analysisIndependent vector analysisSchizophreniaNeuropsychologyFusion frameworkScoresSymmetric data-driven fusion of diffusion tensor MRI: Age differences in white matter
Colmenares A, Hefner M, Calhoun V, Salerno E, Fanning J, Gothe N, McAuley E, Kramer A, Burzynska A. Symmetric data-driven fusion of diffusion tensor MRI: Age differences in white matter. Frontiers In Neurology 2023, 14: 1094313. PMID: 37139071, PMCID: PMC10149813, DOI: 10.3389/fneur.2023.1094313.Peer-Reviewed Original ResearchDiffusion tensor imagingAge differencesExamination of age differencesPattern of age differencesFractional anisotropyRadial diffusivityJoint independent component analysisCognitively healthy adultsWhite matterDiffusion tensor imaging parametersFluid abilitiesPrefrontal WMProcessing speedDiagnostic classificationWM pathologyDiffusion tensor imaging datasetsAging WMUnimodal analysisTensor imagingIndependent component analysisClinical samplesHealthy agingCognitionCorpus callosumHealthy adults