2025
Functional connectome correlates of laterality preferences: Insights into Hand, Foot, and Eye Dominance Across the Lifespan.
Tejavibulya L, Horien C, Fredericks C, Ficek B, Westwater M, Scheinost D. Functional connectome correlates of laterality preferences: Insights into Hand, Foot, and Eye Dominance Across the Lifespan. ENeuro 2025, eneuro.0580-24.2025. PMID: 40473471, DOI: 10.1523/eneuro.0580-24.2025.Peer-Reviewed Original ResearchLateral preferenceFunctional connectomeWhole-brain functional connectomePosterior temporal areasBrain functional connectivityWhole-brain connectomePrefrontal lobeNormative variationCerebellar regionsFunctional connectivityDevelopmental shiftTemporal lobeBrain connectivityWhole-brainLeft-handednessFoot preferenceRight-handednessTemporal areaIncreased connectivityResting-state functional connectomesEffect sizeSignificant associationConnectivity patternsBrain hemispheresHandednessIdentification and external validation of a problem cannabis risk network
Lichenstein S, Kiluk B, Potenza M, Garavan H, Chaarani B, Banaschewski T, Bokde A, Desrivières S, Flor H, Grigis A, Gowland P, Heinz A, Brühl R, Martinot J, Paillère Martinot M, Artiges E, Nees F, Orfanos D, Poustka L, Hohmann S, Holz N, Baeuchl C, Smolka M, Vaidya N, Walter H, Whelan R, Schumann G, Pearlson G, Yip S. Identification and external validation of a problem cannabis risk network. Biological Psychiatry 2025 PMID: 39909136, DOI: 10.1016/j.biopsych.2025.01.022.Peer-Reviewed Original ResearchAlcohol use outcomesCannabis useNeural mechanismsSample of treatment-seeking adultsNeural mechanisms of riskTreatment-seeking adultsCannabis use disorderNon-clinical sampleMechanisms of riskFunctional connectivity dataSample of adolescentsTreatment outcomesAssociated with harmful outcomesPoor treatment outcomesAddiction severityUse disorderEmerging adulthoodWhole-brainCannabisCollege studentsBrain developmentConnectivity dataIdentified networksTreatment approachesAdultsRadiological markers of CSF α-synuclein aggregation in Parkinson’s disease patients
Droby A, Yoffe-Vasiliev A, Atias D, Fraser K, Mabrouk O, Omer N, Bar-Shira A, Gana-Weisz M, Goldstein O, Artzi M, Ben Bashat D, Alcalay R, Orr-Urtreger A, Shirvan J, Cedarbaum J, Giladi N, Mirelman A, Thaler A. Radiological markers of CSF α-synuclein aggregation in Parkinson’s disease patients. Npj Parkinson's Disease 2025, 11: 7. PMID: 39753572, PMCID: PMC11698941, DOI: 10.1038/s41531-024-00854-4.Peer-Reviewed Original ResearchStriatal binding ratiosLRRK2-PD patientsFunctional connectivityLeft fronto-occipital fasciculusCerebrospinal fluidGray matter volumeDeep gray matter volumesRegional brain volumesWhole-brain gray matterNeuromelanin MRIFronto-occipital fasciculusLRRK2-PDWhite matterParkinson's diseaseLeft caudateMatter volumeReduced FCParkinson's disease patientsWhole-brainBrain volumeRadiological markersHealthy controlsFractional anisotropyRadiological measurementsPatients
2024
The early-onset Alzheimer’s disease MRI signature: a replication and extension analysis in early-stage AD
Mehta R, Keith C, Teixeira C, Worhunsky P, Phelps H, Ward M, Miller M, Navia R, Pockl S, Rajabalee N, Coleman M, D’Haese P, Rezai A, Wilhelmsen K, Haut M. The early-onset Alzheimer’s disease MRI signature: a replication and extension analysis in early-stage AD. Cerebral Cortex 2024, 34: bhae475. PMID: 39714256, PMCID: PMC11664631, DOI: 10.1093/cercor/bhae475.Peer-Reviewed Original ResearchConceptsEarly-onset Alzheimer's diseaseLate-onset Alzheimer's diseaseNon-AD pathologyCognitively normal individualsManagement of personsCortical atrophyFunctional statusEarly-stage ADRural populationAlzheimer's diseaseDisease stageLongitudinal studyCortical signatureWhole-brainCortical thinningCortical analysisClinical cohortNormal individualsClinical effectsSignature regionsIndividualsPersonsEarly disease stagesMRI signaturesInterplay 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 timeCortical hubs of highly superior autobiographical memory
Orwig W, Diez I, Bueichekú E, Pedale T, Parente F, Campolongo P, Schacter D, Sepulcre J, Santangelo V. Cortical hubs of highly superior autobiographical memory. Cortex 2024, 179: 14-24. PMID: 39094240, DOI: 10.1016/j.cortex.2024.06.018.Peer-Reviewed Original ResearchConceptsSuperior autobiographical memoryAutobiographical memoryCortical hubsWhole-brain connectivity analysisPattern of increased connectivityResting-state fMRI dataWhole-brain analysisAutobiographical memory networkPosterior cingulate cortexMidline areaSeed-based analysisFunctional brain connectivityGraph theory analysisCingulate cortexNeural underpinningsNeuroimaging studiesEnhance memoryRemembering eventsBrain regionsControl participantsConnectivity analysisFMRI dataBrain connectivityCortical regionsWhole-brainEarly-treatment cerebral blood flow change as a predictive biomarker of antidepressant treatment response: evidence from the EMBARC clinical trial.
Dang Y, Lu B, Vanderwal T, Castellanos F, Yan C. Early-treatment cerebral blood flow change as a predictive biomarker of antidepressant treatment response: evidence from the EMBARC clinical trial. Psychological Medicine 2024, 54: 3053-3062. PMID: 38720516, DOI: 10.1017/s0033291724001156.Peer-Reviewed Original ResearchMajor depressive disorderBrain regionsTreatment of Major Depressive DisorderHamilton Depression Rating Scale scoresBiomarkers of antidepressant treatment responseCerebral blood flowBiosignatures of Antidepressant ResponseDepression Rating Scale scoresSerotonin reuptake inhibitor treatmentAntidepressant treatment responseResponse to antidepressantsTreatment responseRating Scale scoresBiomarkers of treatment responseAssociated with increased cerebral perfusionEstablishing ModeratorsAntidepressant responseAntidepressant effectsDepressive disorderTemporal cortexNeural biomarkersPostcentral regionsCerebral blood flow changesWhole-brainDisabling illnessDefining the r factor for post-trauma resilience and its neural predictors
van Rooij S, Santos J, Hinojosa C, Ely T, Harnett N, Murty V, Lebois L, Jovanovic T, House S, Bruce S, Beaudoin F, An X, Neylan T, Clifford G, Linnstaedt S, Germine L, Bollen K, Rauch S, Haran J, Storrow A, Lewandowski C, Musey P, Hendry P, Sheikh S, Jones C, Punches B, Swor R, Pascual J, Seamon M, Harris E, Pearson C, Peak D, Merchant R, Domeier R, Rathlev N, O’Neil B, Sanchez L, Joormann J, Pizzagalli D, Sheridan J, Harte S, Kessler R, Koenen K, McLean S, Ressler K, Stevens J. Defining the r factor for post-trauma resilience and its neural predictors. Nature Mental Health 2024, 2: 680-693. DOI: 10.1038/s44220-024-00242-0.Peer-Reviewed Original ResearchDefault mode network activityFunctional magnetic resonance imagingResponse to rewardMode network activityPost-trauma resilienceWeeks post-traumaNeurobiological profilesReward valuationReward processingSpecific psychopathologyTransdiagnostic approachBrain mechanismsCognitive functionResilience factorsWhole-brainComponents of resilienceNeural predictorsAURORA studyRewardPost-traumaMagnetic resonance imagingProcess of recoveryNetwork activityResonance imagingPsychopathologyNeurogenetic underpinnings of nicotine use severity: Integrating the brain transcriptomes and GWAS variants via network approaches
Yang B, Xiang B, Wang T, Ma S, Li C. Neurogenetic underpinnings of nicotine use severity: Integrating the brain transcriptomes and GWAS variants via network approaches. Psychiatry Research 2024, 334: 115815. PMID: 38422867, PMCID: PMC11017751, DOI: 10.1016/j.psychres.2024.115815.Peer-Reviewed Original ResearchConceptsMediodorsal nucleus of the thalamusMedial prefrontal cortexPrefrontal cortexNeurogenetic underpinningsDorsolateral prefrontal cortexBrain transcriptomeDrug memoryOrbitofrontal cortexInhibitory controlSmoking severityAssociated with CPDHuman brain transcriptomeMediodorsal nucleusWhole-brainNeurogenetic mechanismsPrimary motor cortexMechanisms of individual variationCortexHub proteinsGenetic riskAmygdalaStriatumMotor cortexOPFCHippocampusSex-driven variability in TSPO-expressing microglia in MS patients and healthy individuals
Laaksonen S, Saraste M, Nylund M, Hinz R, Snellman A, Rinne J, Matilainen M, Airas L. Sex-driven variability in TSPO-expressing microglia in MS patients and healthy individuals. Frontiers In Neurology 2024, 15: 1352116. PMID: 38445263, PMCID: PMC10913932, DOI: 10.3389/fneur.2024.1352116.Peer-Reviewed Original ResearchDistribution volume ratioNormal-appearing white matterMale MS patientsCortical gray matterMS patientsPositron emission tomographyTSPO bindingMultiple sclerosisDisease progressionHealthy individualsClinical disease progressionWhole-brainBrain positron emission tomographySex differencesMales compared to femalesFemale patientsHealthy womenDisability progressionGreater likelihoodGray matterHealthy controlsStudy cohortFemale controlsEmission tomographyBrainBetter with age: Developmental changes in oscillatory activity during verbal working memory encoding and maintenance
Killanin A, Ward T, Embury C, Calhoun V, Wang Y, Stephen J, Picci G, Heinrichs-Graham E, Wilson T. Better with age: Developmental changes in oscillatory activity during verbal working memory encoding and maintenance. Developmental Cognitive Neuroscience 2024, 66: 101354. PMID: 38330526, PMCID: PMC10864839, DOI: 10.1016/j.dcn.2024.101354.Peer-Reviewed Original ResearchWorking memory encodingMemory encodingLeft hemisphere language regionsSternberg verbal working memory taskVerbal working memory taskRight superior temporal regionOlder participantsWorking memory taskWorking memory developmentSuperior temporal regionsSignificant oscillatory responsesWhole-brain mappingDevelopmental effectsMemory taskWorking memoryOscillatory responsesLanguage regionsBrain regionsMemory developmentOscillatory dynamicsTheta powerParticipants aged 6Whole-brainTemporal regionsDevelopmental changesHomological Landscape of Human Brain Functional Sub-Circuits
Duong-Tran D, Kaufmann R, Chen J, Wang X, Garai S, Xu F, Bao J, Amico E, Kaplan A, Petri G, Goni J, Zhao Y, Shen L. Homological Landscape of Human Brain Functional Sub-Circuits. Mathematics 2024, 12: 455. DOI: 10.3390/math12030455.Peer-Reviewed Original ResearchFunctional sub-circuitsHuman brain functional connectivityWhole-brain functional connectivity networksNon-local propertiesWorking memory taskWhole-brain levelBrain functional connectivityNon-localFunctional connectivity networksMemory taskEmotional tasksLimbic networkMode networkFunctional connectivityBrain connectomeWhole-brainFormalismLocal structureMotor tasksConnectivity networksSubject domainSub-circuitsTaskPreliminary Study of White Matter Abnormalities and Associations With the Metabotropic Glutamate Receptor 5 to Distinguish Bipolar and Major Depressive Disorders
Fan S, Asch R, Davis M, DellaGioia N, Cool R, Blumberg H, Esterlis I. Preliminary Study of White Matter Abnormalities and Associations With the Metabotropic Glutamate Receptor 5 to Distinguish Bipolar and Major Depressive Disorders. Chronic Stress 2024, 8: 24705470231225320. PMID: 38250007, PMCID: PMC10798116, DOI: 10.1177/24705470231225320.Peer-Reviewed Original ResearchMetabotropic glutamate receptor 5Bipolar disorderGlutamate receptor 5UF FAUncinate fasciculusFractional anisotropyWhole-brain analysisMultimodal neuroimaging approachDifferentiation of BDDiffusion-weighted MRI scansFrontotemporal dysconnectivityFrontotemporal systemFunctional dysconnectivityDepressive disorderNeurobiological mechanismsMGluR5 levelsWhite matterWhite matter abnormalitiesNeuroimaging approachesWM integrityNeural mechanismsMDDWhole-brainWM abnormalitiesReceptor 5
2023
Functional and Structural Longitudinal Change Patterns in Adolescent Brain
Saha R, Saha D, Fu Z, Silva R, Calhoun V. Functional and Structural Longitudinal Change Patterns in Adolescent Brain. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2023, 00: 1-4. PMID: 38082649, DOI: 10.1109/embc40787.2023.10340079.Peer-Reviewed Original ResearchConceptsFunctional magnetic resonance imagingStructural magnetic resonance imagingFunctional network connectivityWhole-brainGray matterBrain functional magnetic resonance imagingMagnetic resonance imagingAdolescent brainFunctional connectivityResonance imagingMultivariate patternsLongitudinal change patternsUnivariate changesAdolescentsLongitudinal changesBrainIncreasing ageFunctional changesComplementary techniquesNetwork connectivityMining Correlation between Fluid Intelligence and Whole-brain Large Scale Structural Connectivity.
Garai S, Xu F, Duong-Tran D, Zhao Y, Shen L. Mining Correlation between Fluid Intelligence and Whole-brain Large Scale Structural Connectivity. AMIA Joint Summits On Translational Science Proceedings 2023, 2023: 225-233. PMID: 37350917, PMCID: PMC10283120.Peer-Reviewed Original ResearchFluid intelligenceWhole-brain functional connectivity patternsStructural connectivityConnectivity patternsBrain Connectivity ToolboxFunctional connectivity patternsHuman intelligenceStructural connectivity matricesHuman Connectome ProjectStructural connectivity patternsNeural basisGraph theoretical measuresBrain networksConnectivity ToolboxNetwork neuroscienceBrain connectivityWhole-brainConnectome ProjectBrain connectomeYoung adultsStructural connectomeBrainTopological featuresConnectomeIntelligenceAging brain shows joint declines in brain within-network connectivity and between-network connectivity: a large-sample study (N > 6,000)
Du Y, Guo Y, Calhoun V. Aging brain shows joint declines in brain within-network connectivity and between-network connectivity: a large-sample study (N > 6,000). Frontiers In Aging Neuroscience 2023, 15: 1159054. PMID: 37273655, PMCID: PMC10233064, DOI: 10.3389/fnagi.2023.1159054.Peer-Reviewed Original ResearchFunctional network connectivityWithin-network connectivityCognitive control networkFunctional networksIncreased within-network connectivityDecreased within-network connectivityWhole-brain functional networksControl networkReduced functional network connectivityBetween-network connectivityWhole-brain levelNon-pathological agingSub-cortical networksIndependent component analysisBrain functional networksMode networkAging-related changesSensorimotor networkNeuroimaging dataConnectivity declineVisual networkWhole-brainBrain agingAging brainEffects of ageIdentifying Shared Neuroanatomic Architecture Between Cognitive Traits Through Multiscale Morphometric Correlation Analysis
Wen Z, Bao J, Yang S, Risacher S, Saykin A, Thompson P, Davatzikos C, Huang H, Zhao Y, Shen L. Identifying Shared Neuroanatomic Architecture Between Cognitive Traits Through Multiscale Morphometric Correlation Analysis. Lecture Notes In Computer Science 2023, 14394: 227-240. PMID: 38584725, PMCID: PMC10993314, DOI: 10.1007/978-3-031-47425-5_21.Peer-Reviewed Original Research
2018
Task-Evoked Dynamic Network Analysis Through Hidden Markov Modeling
Quinn A, Vidaurre D, Abeysuriya R, Becker R, Nobre A, Woolrich M. Task-Evoked Dynamic Network Analysis Through Hidden Markov Modeling. Frontiers In Neuroscience 2018, 12: 603. PMID: 30210284, PMCID: PMC6121015, DOI: 10.3389/fnins.2018.00603.Peer-Reviewed Original ResearchLarge-scale brain networksTask dataTask-based studiesBrain networksPerception taskWhole-brainFunctional network structureBrain statesFunctional networksElectrophysiological dataHidden Markov ModelMagnetoencephalographyTaskDynamic network analysisDynamic recruitmentTask analysisCognitionMillisecond time scaleAnalysis pipelineMEG datasetBrainTime scales
2011
Neuronal dysfunction and disconnection of cortical hubs in non-demented subjects with elevated amyloid burden
Drzezga A, Becker J, Van Dijk K, Sreenivasan A, Talukdar T, Sullivan C, Schultz A, Sepulcre J, Putcha D, Greve D, Johnson K, Sperling R. Neuronal dysfunction and disconnection of cortical hubs in non-demented subjects with elevated amyloid burden. Brain 2011, 134: 1635-1646. PMID: 21490054, PMCID: PMC3102239, DOI: 10.1093/brain/awr066.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overAlzheimer DiseaseAmyloidAniline CompoundsBenzothiazolesBrain MappingCerebral CortexCognition DisordersFemaleFluorodeoxyglucose F18HumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleMiddle AgedOxygenPositron-Emission TomographyStatistics as TopicThiazolesConceptsWhole-brain connectivityDisruption of functional connectivityCortical hubsEarly functional consequencesMild cognitive impairmentFunctional connectivityAmyloid burdenCognitive impairmentNon-demented older individualsVoxel-based morphometry measuresAmyloid-positive patientsStructural magnetic resonanceDisruption of connectivityEmission tomographyCerebral glucose metabolismAlzheimer-type neurodegenerationAssociated with neuronal dysfunctionClinical Alzheimer's diseaseNon-demented subjectsCognitive symptomsIncreased amyloid burdenBrain regionsFunctional disconnectionNeuronal dysfunctionWhole-brain
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