2025
Unraveling the Neural Landscape of Mental Disorders using Double Functional Independent Primitives (dFIPs)
Soleimani N, Iraji A, Pearlson G, Preda A, Calhoun V. Unraveling the Neural Landscape of Mental Disorders using Double Functional Independent Primitives (dFIPs). Biological Psychiatry Cognitive Neuroscience And Neuroimaging 2025 PMID: 40222638, DOI: 10.1016/j.bpsc.2025.03.015.Peer-Reviewed Original ResearchAutism spectrum disorderFunctional network connectivityBipolar disorderPsychiatric conditionsMental disordersMental illnessResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingConnectivity patternsBrain network alterationsFunctional connectivity patternsNeurobiological underpinningsDepressive disorderEmotion regulationNeural signaturesPsychiatric diagnosisConnectivity alterationsBrain regionsSpectrum disorderCognitive functionNeural landscapeCerebellar connectivitySocial behaviorNetwork alterationsSchizophreniaConnectome-based predictive modeling of early and chronic psychosis symptoms
Foster M, Ye J, Powers A, Dvornek N, Scheinost D. Connectome-based predictive modeling of early and chronic psychosis symptoms. Neuropsychopharmacology 2025, 1-9. PMID: 40016363, DOI: 10.1038/s41386-025-02064-9.Peer-Reviewed Original ResearchConnectome-based predictive modelingPositive and Negative Syndrome ScalePsychosis symptomsSymptom networksSymptom severityBrain networksNeural correlates of CPResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingNegative Syndrome ScaleIdentified group differencesPredicted effect sizeCorrelates of CPGeneral psychopathologyNegative symptomsPositive symptomsSyndrome ScaleFrontoparietal networkNeural correlatesVirtual lesion analysisGroup differencesConnectivity changesEffect sizeLesion analysisLongitudinal studyTransdiagnostic study of dynamic brain activity and connectivity among people with gambling and internet gaming disorders DYNAMIC BRAIN ACTIVITY IN GD AND IGD
Zhou H, He Y, Liu L, Yin J, Xiong A, Leong K, Wu A, Potenza M. Transdiagnostic study of dynamic brain activity and connectivity among people with gambling and internet gaming disorders DYNAMIC BRAIN ACTIVITY IN GD AND IGD. International Journal Of Clinical And Health Psychology 2025, 25: 100547. PMID: 39944189, PMCID: PMC11815891, DOI: 10.1016/j.ijchp.2025.100547.Peer-Reviewed Original ResearchInternet gaming disorder groupInternet gaming disorderIGD participantsFunctional magnetic resonance imagingDynamic brain activityGambling disorderHC participantsBrain activityTransdiagnostic studiesFrontal gyrusLeft triangular inferior frontal gyrusFeatures of behavioral addictionsResting-state functional magnetic resonance imagingTriangular inferior frontal gyrusInferior frontal gyrusCombination of self-reportHealthy controlsPositive playBehavioral addictionsSelf-reported indicatorsNeural measuresGaming disorderDiagnostic groupsBrain connectivitySelf-reportInfants’ Resting-State Functional Connectivity and Event-Related Potentials: A Multimodal Approach to Investigating the Neural Basis of Infant Novelty Detection
Kanel D, Morales S, Altman K, Richards J, Winkler A, Pine D, Fox N, Filippi C. Infants’ Resting-State Functional Connectivity and Event-Related Potentials: A Multimodal Approach to Investigating the Neural Basis of Infant Novelty Detection. Developmental Psychology 2025 PMID: 39760730, DOI: 10.1037/dev0001892.Peer-Reviewed Original ResearchFunctional magnetic resonance imagingEvent-related potentialsEvent-related potential dataResting-state functional connectivityMismatch responsesFunctional connectivityRegions-of-interestRs-FCThree-stimulus auditory oddball taskResting-state functional magnetic resonance imagingFunctional magnetic resonance imaging dataSuperior parietal cortexPosterior cingulate cortexVentral attention networkSuperior parietal lobuleBilateral auditory corticesAuditory oddball taskNovelty detectionNovelty processingCingulate cortexNeural basisParietal lobuleNovel stimuliP3 responseSomatomotor network
2024
Brain networks and intelligence: A graph neural network based approach to resting state fMRI data
Thapaliya B, Akbas E, Chen J, Sapkota R, Ray B, Suresh P, Calhoun V, Liu J. Brain networks and intelligence: A graph neural network based approach to resting state fMRI data. Medical Image Analysis 2024, 101: 103433. PMID: 39708510, PMCID: PMC11877132, DOI: 10.1016/j.media.2024.103433.Peer-Reviewed Original ResearchConceptsGraph neural networksNeural networkGraph isomorphism networkGraph convolutional layersGraph convolutional networkMachine learning modelsNetwork connectivity matrixCognitive processesConvolutional layersConvolutional networkPrediction taskModel architectureGraph architectureAdolescent Brain Cognitive Development datasetResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingLearning modelsMiddle frontal gyrusPredicting individual differencesResting state fMRI dataPredictive intelligenceIntelligenceNetworkFunctional network connectivity matricesArchitectureMultimodal 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 regressionBrain networks and intelligence: A graph neural network based approach to resting state fMRI data
Thapaliya B, Akbas E, Chen J, Sapkota R, Ray B, Suresh P, Calhoun V, Liu J. Brain networks and intelligence: A graph neural network based approach to resting state fMRI data. Medical Image Analysis 2024, 101: 103433. PMID: 37986729, PMCID: PMC10659448, DOI: 10.1016/j.media.2024.103433.Peer-Reviewed Original ResearchGraph neural networksNeural networkGraph isomorphism networkGraph convolutional layersGraph convolutional networkMachine learning modelsMean square errorNetwork connectivity matrixCognitive processesConvolutional layersConvolutional networkPrediction taskModel architectureGraph architectureAdolescent Brain Cognitive Development datasetResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingLearning modelsMiddle frontal gyrusPredicting individual differencesResting state fMRI dataPredictive intelligenceIntelligenceNetworkFunctional network connectivity matricesFrequency modulation increases the specificity of time-resolved connectivity: A resting-state fMRI study
Faghiri A, Yang K, Faria A, Ishizuka K, Sawa A, Adali T, Calhoun V. Frequency modulation increases the specificity of time-resolved connectivity: A resting-state fMRI study. Network Neuroscience 2024, 8: 734-761. PMID: 39355435, PMCID: PMC11349031, DOI: 10.1162/netn_a_00372.Peer-Reviewed Original ResearchSliding window Pearson correlationTime-resolved networksSingle sideband modulationTime-resolved connectivityResting-state fMRI studiesSideband modulationFunctional magnetic resonance imagingFunctional network connectivityResting-state functional magnetic resonance imagingActivity time seriesTypical controlsFrequency modulationLow-frequency informationStateEpisode of psychosisNetwork connectivityHuman brainSub-corticalSuperior performanceFMRI studyCortical regionsLongitudinal development of resting-state functional connectivity in adolescents with and without internalizing disorders
Roelofs E, Bas-Hoogendam J, Winkler A, van der Wee N, Vermeiren R. Longitudinal development of resting-state functional connectivity in adolescents with and without internalizing disorders. Neuroscience Applied 2024, 3: 104090. PMID: 39634556, PMCID: PMC11615185, DOI: 10.1016/j.nsa.2024.104090.Peer-Reviewed Original ResearchRight laterobasal amygdalaLaterobasal amygdalaWhole-brain networksAmygdala subregionsFunctional connectivityCentromedial amygdalaSymptom changeFrontal poleInternalizing disordersPostcentral gyrusResting-state functional magnetic resonance imagingResting-state functional connectivityFunctional magnetic resonance imagingICA-derived networksClinically representative sampleFC developmentNonspecific treatment effectsRs-fMRI scansIndependent component analysisResting-state networksLongitudinal developmentCare-as-usualComorbid anxietyNeuroimaging researchBilateral seedsHuman brain state dynamics are highly reproducible and associated with neural and behavioral features
Lee K, Ji J, Fonteneau C, Berkovitch L, Rahmati M, Pan L, Repovš G, Krystal J, Murray J, Anticevic A. Human brain state dynamics are highly reproducible and associated with neural and behavioral features. PLOS Biology 2024, 22: e3002808. PMID: 39316635, PMCID: PMC11421804, DOI: 10.1371/journal.pbio.3002808.Peer-Reviewed Original ResearchConceptsCo-activation patternsResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingBehavioral featuresNeural variationsMoment-to-moment changesSingle-subject levelBrain state dynamicsEmotion regulationHealthy young adultsBehavioral phenotypesCognitive functionSubstance useNeural activityNeuroimaging markersNeural featuresYoung adultsMagnetic resonance imagingCo-activationResonance imagingCo-variationNeuroimagingIndividualsEmotionsFunctional outcomesThe White Matter Integrity and Functional Connection Differences of Fornix (Cres)/Stria Terminalis in Individuals with Mild Cognitive Impairment Induced by Occupational Aluminum Exposure
Zhang F, Li Y, Chen R, Shen P, Wang X, Meng H, Du J, Yang G, Liu B, Niu Q, Zhang H, Tan Y. The White Matter Integrity and Functional Connection Differences of Fornix (Cres)/Stria Terminalis in Individuals with Mild Cognitive Impairment Induced by Occupational Aluminum Exposure. ENeuro 2024, 11: eneuro.0128-24.2024. PMID: 39142823, PMCID: PMC11360986, DOI: 10.1523/eneuro.0128-24.2024.Peer-Reviewed Original ResearchConceptsMild cognitive impairmentFunctional connectivityCognitive impairmentNeural mechanismsRight inferior frontal gyrusResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingInferior frontal gyrusRight anterior cingulateRight temporal poleFunctional connectivity differencesWhite matter integrityRight sagittal stratumFractional anisotropy valuesAnterior cingulateFrontal gyrusDiffusion tensor imagingMontreal Cognitive AssessmentTemporal poleWhite matterWM integrityPlasma Al concentrationParacingulate gyriCognitive AssessmentSagittal stratumAssociation between the oral microbiome and brain resting state connectivity in schizophrenia
Lin D, Fu Z, Liu J, Perrone-Bizzozero N, Hutchison K, Bustillo J, Du Y, Pearlson G, Calhoun V. Association between the oral microbiome and brain resting state connectivity in schizophrenia. Schizophrenia Research 2024, 270: 392-402. PMID: 38986386, DOI: 10.1016/j.schres.2024.06.045.Peer-Reviewed Original ResearchOral microbiomeMicrobial speciesArea under curveResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingMicrobial 16S rRNA sequencingBrain circuit dysfunctionHealthy controlsBrain functional connectivity alterationsFunctional connectivity alterationsFunctional neuroimaging techniquesHypothalamic-pituitary-adrenal axisBrain functional connectivityFunctional network connectivityBrain functional activityBrain functional network connectivityHealthy control subjectsNeurotransmitter signaling pathwaysBeta diversityMicrobiome communitiesOral microbiome dysbiosisRRNA sequencingCircuit dysfunctionConnectivity alterationsSchizophreniaIdentifying 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 ageFMRIBeyond Artifacts: Rethinking Motion-Related Signals in Resting-State fMRI Analysis
Kumar S, Kinsey S, Jensen K, Bajracharya P, Calhoun V, Iraji A. Beyond Artifacts: Rethinking Motion-Related Signals in Resting-State fMRI Analysis. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-4. PMID: 40040138, DOI: 10.1109/embc53108.2024.10782518.Peer-Reviewed Original ResearchConceptsFunctional network connectivityBOLD time seriesImpact of head motionHead motion dataLarge-scale brain networksIntrinsic brain functional connectivityResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingFunctional brain connectivityResting-state fMRI analysisRsfMRI dataBOLD fMRIHead motionBrain functional connectivityHealthy controlsBOLD signalBrain connectivityBrain networksMotion dataFMRI analysisFunctional connectivityClinical populationsMotion-related signalsClinical implicationsBOLDFindings 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 analysisDeficitsA 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-beingAbnormal 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 methodCoupling between Time-Varying EEG Spectral Bands and Spatial Dynamic FMRI Networks
Phadikar S, Pusuluri K, Jensen K, Wu L, Iraji A, Calhoun V. Coupling between Time-Varying EEG Spectral Bands and Spatial Dynamic FMRI Networks. 2024, 00: 1-4. DOI: 10.1109/isbi56570.2024.10635622.Peer-Reviewed Original ResearchFunctional brain networksDynamic brain networksBrain networksSpectral propertiesDynamics of functional brain networksFMRI networksSpectral bandsSpatial dimensionsResting-state functional magnetic resonance imagingConnectivity matrixCouplingBandFunctional magnetic resonance imagingDynamic networksSimultaneous electroencephalographyPersonalized treatment approachesElectroencephalography spectral powerResting stateMagnetic resonance imagingDecoupling of gray and white matter functional networks in cognitive impairment induced by occupational aluminum exposure
Zhang F, Li L, Liu B, Shao Y, Tan Y, Niu Q, Zhang H. Decoupling of gray and white matter functional networks in cognitive impairment induced by occupational aluminum exposure. NeuroToxicology 2024, 103: 1-8. PMID: 38777096, DOI: 10.1016/j.neuro.2024.05.001.Peer-Reviewed Original ResearchExecutive control networkFunctional connectivityCognitive impairmentCognitive functionTrail Making Test Part AResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingControl networkDecreased FCsReduced functional connectivityGray matterHuman cognitive functionsCognitive impairment groupExecutive controlNeurobiological mechanismsLimbic networkMontreal Cognitive AssessmentWhite matterCognitive AssessmentImpairment groupFunctional networksMagnetic resonance imagingImpairmentPart ACognitionA 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 abnormalities
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