2024
Multimodal predictive modeling: Scalable imaging informed approaches to predict future brain health
Ajith M, Spence J, Chapman S, Calhoun V. Multimodal predictive modeling: Scalable imaging informed approaches to predict future brain health. Journal Of Neuroscience Methods 2024, 414: 110322. PMID: 39608579, PMCID: PMC11687617, DOI: 10.1016/j.jneumeth.2024.110322.Peer-Reviewed Original ResearchStatic functional network connectivityHealth constructsNeuroimaging dataBrain healthResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingSupport vector regressionFunctional network connectivityRandom forestCognitive performanceAssessment-onlyRs-fMRINeural patternsBehavioral outcomesBehavioral dataDiverse data sourcesNeural connectionsPsychological stateTraining stageMagnetic resonance imagingLongitudinal changesNetwork connectivityBrainPerformance evaluationVector regressionIdentifying Canonical multi-scale Intrinsic Connectivity Networks in Infant resting-state fMRI and their Association with Age
Bajracharya P, Faghiri A, Fu Z, Calhoun V, Shultz S, Iraji A. Identifying Canonical multi-scale Intrinsic Connectivity Networks in Infant resting-state fMRI and their Association with Age. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-4. PMID: 40039283, DOI: 10.1109/embc53108.2024.10782404.Peer-Reviewed Original ResearchConceptsIntrinsic connectivity networksStatic functional network connectivitySubject-specific intrinsic connectivity networksResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingFunctional brain organizationResting-state fMRIFunctional network connectivityConnectivity networksCognitive domainsCognitive processesBrain organizationSub-corticalRsfMRI dataIndependent component analysisMagnetic resonance imagingNeuromarkersDistinct patternsMotor controlNeurodevelopmental disabilitiesResonance imagingEarly identificationSensory perceptionAssociated with ageFMRIA Trifecta of Deep Learning Models: Assessing Brain Health by Integrating Assessment and Neuroimaging Data
Ajith M, M. Aycock D, B. Tone E, Liu J, B. Misiura M, Ellis R, M. Plis S, Z. King T, M. Dotson V, Calhoun V. A Trifecta of Deep Learning Models: Assessing Brain Health by Integrating Assessment and Neuroimaging Data. Aperture Neuro 2024, 4 DOI: 10.52294/001c.118576.Peer-Reviewed Original ResearchStatic functional network connectivityBrain health indexBrain healthResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingPsychological assessment measuresAssessment dataFunctional network connectivityMental health disordersBrain systemsEvaluating brain healthNeuroimaging dataRs-fMRINeural patternsPhysical well-beingCognitive declineAssessment measuresHealth disordersVariational autoencoderNeuroimagingHealthy brainBrainMagnetic resonance imagingTesting phaseWell-beingThe overlap across psychotic disorders: A functional network connectivity analysis
Dini H, Bruni L, Ramsøy T, Calhoun V, Sendi M. The overlap across psychotic disorders: A functional network connectivity analysis. International Journal Of Psychophysiology 2024, 201: 112354. PMID: 38670348, PMCID: PMC11163820, DOI: 10.1016/j.ijpsycho.2024.112354.Peer-Reviewed Original ResearchConceptsFunctional network connectivitySchizoaffective disorderPsychotic disordersHealthy controlsBipolar-Schizophrenia NetworkFunctional network connectivity analysisStatic functional network connectivityResting-state fMRINetwork connectivity analysisPatterns of activityPsychiatric disordersDisorder groupSchizophreniaConnectivity analysisHC groupBipolarConnectivity patternsDisordersPatient groupSymptom scoresGroup of patientsPANSSSchizoaffectiveFMRINetwork connectivityA deep learning approach for mental health quality prediction using functional network connectivity and assessment data
Ajith M, Aycock D, Tone E, Liu J, Misiura M, Ellis R, Plis S, King T, Dotson V, Calhoun V. A deep learning approach for mental health quality prediction using functional network connectivity and assessment data. Brain Imaging And Behavior 2024, 18: 630-645. PMID: 38340285, DOI: 10.1007/s11682-024-00857-y.Peer-Reviewed Original ResearchStatic functional network connectivityMental health qualityFunctional network connectivityMental health categoriesRs-fMRIMental healthPatterns of abnormal connectivityHealth categoriesHealth qualityDevelopment of personalized interventionsManagement of mental healthResting-state fMRIMeasure mental healthUK Biobank datasetNeural patternsBrain healthVisual domainAbnormal connectionPersonalized interventionsBiobank datasetTreatment responseHealthNetwork connectivityBehavioral aspectsAssessment data
2023
Network Differential in Gaussian Graphical Models from Multimodal Neuroimaging Data*
Falakshahi H, Rokham H, Miller R, Liu J, Calhoun V. Network Differential in Gaussian Graphical Models from Multimodal Neuroimaging Data*. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2023, 00: 1-6. PMID: 38083176, DOI: 10.1109/embc40787.2023.10340856.Peer-Reviewed Original ResearchConceptsStatic functional network connectivityGaussian graphical modelsBrain disordersBrain graphsModel of schizophreniaMiddle temporal gyrusMechanisms of brain disordersFunctional network connectivityGray matter featuresBrain network analysisTemporal gyrusGroup graphPath-based analysisCerebellar regionsGraph theory approachSchizophreniaMultimodal studiesGraphical modelsNetwork connectivityNetwork differentiationGray matterGraphical metricsControl graphPairwise edgesBrainFunctional Network Connectivity Based Mental Health Category Prediction from Rest-fMRI Data
Ajith M, Calhoun V. Functional Network Connectivity Based Mental Health Category Prediction from Rest-fMRI Data. 2023, 00: 1-5. DOI: 10.1109/isbi53787.2023.10230721.Peer-Reviewed Original ResearchFunctional network connectivityMental healthResting fMRIStatic functional network connectivityMental health classesMental health categoriesBrain networksMental health scoresBehavioral changesBehavior modificationSignificant health issueBrainHealthy habitsHealth scoresHealth categoriesHealth classesHealth issuesIndividual levelFMRICategory predictionNetwork connectivityNeuroimagingHealth
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