2025
Modularity Measures of Functional Brain Networks Predict Individual Differences in Long‐Term Memory
Zhou M, Chun M, Lin Q. Modularity Measures of Functional Brain Networks Predict Individual Differences in Long‐Term Memory. European Journal Of Neuroscience 2025, 61: e70052. PMID: 40091538, DOI: 10.1111/ejn.70052.Peer-Reviewed Original ResearchConceptsLong-term memoryPredicting individual differencesRecollection memoryIndividual differencesBrain networksLong-term memory performanceLong-term memory capacityMeasures of brain activityBrain functional organizationBrain functional connectivityMode networkBrain activityFunctional connectivityConnector hubsMemoryFunctional organizationBrainModularity measureRecollectionConnectivity featuresEncodingCognitionNeuroanatomyLocal measurementsDifferencesConnectome-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 studyStatic 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 conditionsNeural Rewiring of Resilience: The Effects of Combat Deployment on Functional Network Architecture
Yair N, Zalmenson T, Azriel O, Shamai-Leshem D, Alon Y, Tik N, Tatsa-Laur L, Ben-Yehuda A, Pine D, Winkler A, Tavor I, Bar-Haim Y. Neural Rewiring of Resilience: The Effects of Combat Deployment on Functional Network Architecture. Biological Psychiatry Cognitive Neuroscience And Neuroimaging 2025 PMID: 39824285, DOI: 10.1016/j.bpsc.2024.12.017.Peer-Reviewed Original ResearchFunctional magnetic resonance imaging studyBetween-network functional connectivityTrauma-related psychopathologyEffects of combat deploymentBetween-network connectivityVentral attention networkBrain functional architectureFunctional brain networksMagnetic resonance imaging studiesFunctional network architectureCognitive controlCombat exposureNeural basisBrain networksCombat deploymentFunctional connectivityResilient individualsGroup of university studentsResilient participantsAttention networkNeural adaptationSignificant groupComparison groupLongitudinal studyFunctional architectureImpaired spatial dynamic functional network connectivity and neurophysiological correlates in functional hemiparesis
Premi E, Cantoni V, Benussi A, Iraji A, Calhoun V, Corbo D, Gasparotti R, Tinazzi M, Borroni B, Magoni M. Impaired spatial dynamic functional network connectivity and neurophysiological correlates in functional hemiparesis. NeuroImage Clinical 2025, 45: 103731. PMID: 39764901, PMCID: PMC11762193, DOI: 10.1016/j.nicl.2025.103731.Peer-Reviewed Original ResearchDynamic functional network connectivitySomatomotor networkSalience networkFunctional network connectivityGABAergic neurotransmissionResting-state functional MRI scansResting-state fMRI dataFunctional MRI scansDynamic brain statesBrain network dynamicsStatic functional connectivityDynamic brain networksBrain networksGlutamatergic transmissionNeurophysiological correlatesFunctional connectivityTranscranial magnetic stimulation protocolFMRI dataGABAergic inhibitionMagnetic stimulation protocolBrain statesNeurotransmissionHealthy controlsDMNNetwork connectivity
2024
The impact of functional correlations on task information coding
Ito T, Murray J. The impact of functional correlations on task information coding. Network Neuroscience 2024, 8: 1331-1354. PMID: 39735511, PMCID: PMC11675092, DOI: 10.1162/netn_a_00402.Peer-Reviewed Original ResearchNoise correlationsTrial-to-trialBrain networksFunctional brain networksFunctional correlatesFMRI networksSignal correlationNeural correlatesBrain regionsInformation codingTask selectionFMRI datasetsTask informationNeural unitsCorrelated changesCoding frameworkBrainInvestigate relationshipsNetworkFMRINoiseEffect of brain network scale on Persistence Cycles: An ADNI comparative study
Garai S, Liu M, Xu F, Goñi J, Duong‐Tran D, Zhao Y, Shen L, for the ADNI. Effect of brain network scale on Persistence Cycles: An ADNI comparative study. Alzheimer's & Dementia 2024, 20: e092343. PMCID: PMC11716291, DOI: 10.1002/alz.092343.Peer-Reviewed Original ResearchStructural connectomeFunctional connectomeBOLD signal fluctuationsBrain networksHomologation cycleAlzheimer's diseaseDiffusion tensor imagingStages of AD progressionAverage persistenceFMRI neuroimagingTopological featuresAlzheimer's Disease Neuroimaging InitiativeStages of disease progressionSignal fluctuationsConnectomeGroup differencesResolution scaleAD progressionImage resolutionResolution imagesTopological pointIncrease image resolutionDeath timeRegion-of-interestBarcodingAssociations between parental psychopathology and youth functional emotion regulation brain networks
Karl V, Beck D, Eilertsen E, Morawetz C, Wiker T, Aksnes E, Norbom L, Ferschmann L, MacSweeney N, Voldsbekk I, Andreassen O, Westlye L, Gee D, Engen H, Tamnes C. Associations between parental psychopathology and youth functional emotion regulation brain networks. Developmental Cognitive Neuroscience 2024, 70: 101476. PMID: 39541797, PMCID: PMC11609324, DOI: 10.1016/j.dcn.2024.101476.Peer-Reviewed Original ResearchParental psychopathologyYouth psychopathologyEmotion regulationAssociated with children's emotion regulationResting-state functional magnetic resonance imaging dataAdolescent Brain Cognitive Development StudyIntergenerational transmission of psychopathologyAssociated with lower connectivityFunctional magnetic resonance imaging dataTransmission of psychopathologyChildren's emotion regulationCognitive Development StudyMagnetic resonance imaging dataParental mental healthPFC networksPsychopathologyBrain networksParental internalizingMediation analysisCognitive aspectsMental healthConnectivity patternsIntergenerational transmissionNetwork connectivityYouthSex‐specific topological structure associated with dementia via latent space estimation
Wang S, Wang Y, Xu F, Tian X, Fredericks C, Shen L, Zhao Y, Initiative F. Sex‐specific topological structure associated with dementia via latent space estimation. Alzheimer's & Dementia 2024, 20: 8387-8401. PMID: 39530632, PMCID: PMC11667551, DOI: 10.1002/alz.14266.Peer-Reviewed Original ResearchAging-dependent loss of functional connectivity in a mouse model of Alzheimer’s disease and reversal by mGluR5 modulator
Mandino F, Shen X, Desrosiers-Grégoire G, O’Connor D, Mukherjee B, Owens A, Qu A, Onofrey J, Papademetris X, Chakravarty M, Strittmatter S, Lake E. Aging-dependent loss of functional connectivity in a mouse model of Alzheimer’s disease and reversal by mGluR5 modulator. Molecular Psychiatry 2024, 1-16. PMID: 39424929, DOI: 10.1038/s41380-024-02779-z.Peer-Reviewed Original ResearchFunctional connectivity deficitsConnectivity deficitsFunctional connectivityBrain connectivityAllosteric modulators of mGluR5Alzheimer's diseaseDefault-mode networkModulation of mGluR5Loss of functional connectivityResting-state fMRIApplication of fMRIWild-type controlsAged AD miceMouse model of Alzheimer's diseaseAD-related changesAD miceModel of Alzheimer's diseaseAssociated with synaptic damageMGluR5 modulationMonths of ageFMRI measurementsAmyloid accumulationDecreased connectivityBrain networksSilent allosteric modulatorsBrain-phenotype predictions of language and executive function can survive across diverse real-world data: Dataset shifts in developmental populations
Adkinson B, Rosenblatt M, Dadashkarimi J, Tejavibulya L, Jiang R, Noble S, Scheinost D. Brain-phenotype predictions of language and executive function can survive across diverse real-world data: Dataset shifts in developmental populations. Developmental Cognitive Neuroscience 2024, 70: 101464. PMID: 39447452, PMCID: PMC11538622, DOI: 10.1016/j.dcn.2024.101464.Peer-Reviewed Original ResearchBrain-phenotype associationsConnectome-based predictive modelingBrain-behavior associationsPrediction of languagePhiladelphia Neurodevelopmental CohortHealthy Brain NetworkClinical symptom burdenFMRI taskHuman Connectome ProjectExecutive functionBehavioral measuresDevelopmental populationsNeurodevelopmental CohortBrain networksDevelopmental sampleConnectome ProjectResearch settingsGeneralizabilitySymptom burdenExternal validationFMRIClinical settingAssociationEthnic minority representationTaskEnhancing cognitive performance prediction by white matter hyperintensity connectivity assessment
Petersen M, Coenen M, DeCarli C, De Luca A, van der Lelij E, Weiner M, Aisen P, Petersen R, Weiner M, Aisen P, Petersen R, Jack C, Jagust W, Landau S, Rivera-Mindt M, Okonkwo O, Shaw L, Lee E, Toga A, Beckett L, Harvey D, Green R, Saykin A, Nho K, Perrin R, Tosun D, Sachdev P, Green R, Drake E, Montine T, Conti C, Weiner M, Nosheny R, Sacrey D, Fockler J, Miller M, Conti C, Kwang W, Jin C, Diaz A, Ashford M, Flenniken D, Petersen R, Aisen P, Rafii M, Raman R, Jimenez G, Donohue M, Salazar J, Fidell A, Boatwright V, Robison J, Zimmerman C, Cabrera Y, Walter S, Clanton T, Shaffer E, Webb C, Hergesheimer L, Smith S, Ogwang S, Adegoke O, Mahboubi P, Pizzola J, Jenkins C, Beckett L, Harvey D, Donohue M, Saito N, Diaz A, Hussen K, Okonkwo O, Rivera-Mindt M, Amaza H, Thao M, Parkins S, Ayo O, Glittenberg M, Hoang I, Germano K, Strong J, Weisensel T, Magana F, Thomas L, Guzman V, Ajayi A, Benedetto J, Talavera S, Jack C, Felmlee J, Fox N, Thompson P, DeCarli C, Forghanian-Arani A, Borowski B, Reyes C, Hedberg C, Ward C, Schwarz C, Reyes D, Gunter J, Moore-Weiss J, Kantarci K, Matoush L, Senjem M, Vemuri P, Reid R, Malone I, Thomopoulos S, Nir T, Jahanshad N, Knaack A, Fletcher E, Harvey D, Tosun-Turgut D, Chen S, Choe M, Crawford K, Yushkevich P, Das S, Jagust W, Landau S, Koeppe R, Rabinovici G, Villemagne V, LoPresti B, Perrin R, Morris J, Franklin E, Bernhardt H, Cairns N, Taylor-Reinwald L, Shaw L, Lee E, Virginia Lee M, Korecka M, Brylska M, Wan Y, Trojanowki J, Toga A, Crawford K, Neu S, Saykin A, Nho K, Foroud T, Jo T, Risacher S, Craft H, Apostolova L, Nudelman K, Faber K, Potter Z, Lacy K, Kaddurah-Daouk R, Shen L, Karlawish J, Erickson C, Grill J, Largent E, Harkins K, Weiner M, Thal L, Kachaturian Z, Frank R, Snyder P, Buckholtz N, Hsiao J, Ryan L, Molchan S, Khachaturian Z, Carrillo M, Potter W, Barnes L, Bernard M, González H, Ho C, Hsiao J, Jackson J, Masliah E, Masterman D, Okonkwo O, Perrin R, Ryan L, Silverberg N, Silbert L, Kaye J, White S, Pierce A, Thomas A, Clay T, Schwartz D, Devereux G, Taylor J, Ryan J, Nguyen M, DeCapo M, Shang Y, Schneider L, Munoz C, Ferman D, Conant C, Martin K, Oleary K, Pawluczyk S, Trejo E, Dagerman K, Teodoro L, Becerra M, Fairooz M, Garrison S, Boudreau J, Avila Y, Brewer J, Jacobson A, Gama A, Kim C, Little E, Frascino J, Ferng N, Trujillo S, Heidebrink J, Koeppe R, MacDonald S, Malyarenko D, Ziolkowski J, O'Connor J, Robert N, Lowe S, Rogers V, Petersen R, Hackenmiller B, Boeve B, Albers C, Kreuger C, Jones D, Knopman D, Botha H, Magnuson J, Graff-Radford J, CrawleyW K, Schumacher M, McKinzie S, Smith S, Helland T, Lowe V, Ramanan V, Pavlik V, Faircloth J, Bishop J, Nath J, ChaudharyP M, Kataki M, Yu M, Pacini N, Barker R, Brooks R, Aggarwal R, Honig L, Stern Y, Mintz A, Cordona J, Hernandez M, Long J, Arnold A, Groves A, Middleton A, Vogler B, McCurry C, Mayo C, Raji C, Amtashar F, KlempW H, Elmore H, Ruszkiewicz J, Kusuran J, Stewart J, Horenkamp J, Greeson J, Wever K, Vo K, Larkin K, Rao L, Schoolcraft L, Gallagher L, Paczynski M, McMillan M, Holt M, Gagliano N, Henson R, LaBarge R, Swarm R, MunieN S, Cepeda S, WintertonN S, Hegedus S, Wilson T, Harte T, Bonacorsi Z, Geldmacher D, Watkins A, BargerRT B, Smelser B, Bates C, Stover C, McKinley E, Ikner G, Hendrix H, Cooper H, Mahaffey J, Robbins L, Ashley L, Natelson-Love M, Carter P, Solomon V, Grossman H, Groome A, Ardolino A, Kaplan A, Sheppard F, Burgos-Rivera G, Garcia-Camilo G, Lim J, Neugroschl J, Jackson K, Evans K, Soleimani L, Sano M, Ghesani N, Binder S, Apuango X, Sood A, Troutman A, Blanchard K, Richards A, Nelson G, HendricksonN K, Yurko E, Plenge J, Rufo V, Shah R, Duara R, Lynch B, Chirinos C, Dittrich C, Campbell D, Mejia D, Perez G, Colvee H, Gonzalez J, Gondrez J, Knaack J, Acevedo M, Cereijo M, Greig-Custo M, Villar M, Wishnia M, Detling S, Barker W, Albert M, Moghekar A, Rodzon B, Demsky C, Pontone G, Pekar J, Farrington L, Pomper M, Johnson N, Alo T, Sadowski M, Ulysse A, Masurkar A, Marti B, Mossa D, Geesey E, Petrocca E, Schulze E, Wong J, Boonsiri J, Kenowsky S, Martinez T, Briglall V, Doraiswamy Murali P, Nwosu A, Adhikari A, Hellegers C, Petrella J, James O, Wong T, Hawk T, Vaishnavi S, McCoubrey H, Nasrallah I, Rovere R, Maneval J, Robinson E, Rivera F, Uffelman J, Combs M, O'Donnell P, Manning S, King R, NietoN A, Glueck A, Mandal A, Swain A, Gamble B, Beverly Meacham M, Forenback D, Ross D, Cheatham E, Hartman E, Cornell G, Harp J, Ashe L, Goins L, Watts L, Yazell M, Mandal P, BucklerN R, Vincent S, Rudd T, Lopez O, Malia Arlene A, Chiado C, Zik C, Ruszkiewicz J, Savage K, Fenice L, Oakley M, Tacey P, Berman S, Bowser S, Hegedus S, Saganis X, Porsteinsson A, Mathewson A, Widman A, Holvey B, Clark E, Morales E, Iris Young C, Ruszkiewicz J, Hopkins K, Martin K, Kowalski N, Hunt R, Calzavara R, Kurvach R, Stephen D'Ambrosio C, Thai G, Vides B, Lieb B, McAdams-Ortiz C, Toso C, Mares I, Moorlach K, Liu L, Corona M, Nguyen M, Tallakson M, McDonnell M, Rangel M, Basheer N, Place P, Romero R, Tam S, Nguyen T, Thomas A, Frolov A, Khera A, Browning A, Kelley B, Courtney Dawson R, Mathews D, Most E, Phillips E, Nguyen L, Nunez M, Miller M, Jones Matthew R, Martinez N, Rebecca Logan C, McColl R, Pham S, Fox T, Moore T, Levey A, Brown A, Kippels A, Ellison A, Lyons C, Hales C, Parry C, Williams C, McCorkle E, Harris G, Rose H, Jooma I, Al-Amin J, Lah J, Webster J, Swiniarski J, Chapman L, Donnelly L, Mariotti L, Locke M, Vaughn P, Penn R, Carpentier S, Yeboah S, Basadre S, Malakauskas S, Lyron S, Villinger T, Burney T, Burns J, Ala Abusalim C, Dahlgren A, Montero A, Arthur A, Dooly H, Kreszyn K, Berner K, Gillen L, Scanlan M, Madison M, Mathis N, Switzer P, Townley R, Fikru S, Sullivan S, Wright E, Beigi M, Daley A, Ko A, Luong B, Nyborg G, Morales J, Durbin K, Garcia L, Parand L, Macias L, Monserratt L, Farchi M, Wu P, Hernandez R, Rodriguez T, Graff-Radford N, Marolt A, Thomas A, Aloszka D, Moncayo E, Westerhold E, Day G, Chrestensen K, Imhansiemhonehi M, McKinzie S, Stephens S, Grant S, Brosch J, Perkins A, Saunders A, Kovac D, Polson H, Mwaura I, Mejia K, Britt K, King K, Nichols K, Lawrence K, Rankin L, Farlow M, Wiesenauer P, Bryant R, Herring S, Lynch S, Wilson S, Day T, Korst W, van Dyck C, Mecca A, Miller A, Brennan A, Khan A, Ruan A, Gunnoud C, Mendonca C, Raynes-Goldfinger D, Salardini E, Hidalgo E, Cooper E, Singh E, Murphy E, May J, Stanhope J, Lam J, Waszak J, Nelsen K, Sacaza K, Hasbani M, Donahue M, Chen M, Barcelos N, Eigenberger P, Bonomi R, O'Dell R, Jefferson S, Khasnavis S, Smilowitz S, DeStefano S, Good S, Camarro T, Clayton V, Cavrel Y, Lu Y, Chertkow H, Bergman H, Hosein C, Black S, Kapadia A, Bhan A, Lam B, Scott C, Gabriel G, Bray J, Zotovic L, Gutierrez M, Masellis M, Farshadi M, Gui M, Mitchellc M, Taylor R, Endre R, Taghi-Zada Z, Hsiung R, English C, Kim E, Yau E, Tong H, Barlow L, Jennings L, Assaly M, Nunes P, Marian T, Kertesz A, Rogers J, Trost D, Wint D, Bernick C, Munic D, Grant I, Korkoyah A, Raja A, Lapins A, Ryan C, Pejic J, Basham K, Lukose L, Haddad L, Quinlan L, Houghtaling N, Sadowsky C, Martinez W, Villena T, Reynolds B, Forero A, Ward C, Brennan E, Figueroa E, Esposito G, Mallory J, Johnson K, Turner K, Seidenberg K, McCann K, Bassett M, Chadwick M, Turner R, Bean R, Sharma S, Marshall G, Haviari A, Alison Pietras C, Wallace B, Munro C, Rivera-Delpin G, Hustead H, Levesque I, Ramirez J, Karen Nolan M, Glennon K, Palou M, Erkkinen M, DaSilva N, Friedman P, Silver R, Salazar R, Polleys R, McGinnis S, Gale S, Hall T, Luu T, Chao S, Lin E, Coleman J, Epperson K, Vasanawala M, Atri A, Rangel A, Evans B, Monarrez C, Cline C, Liebsack C, Bandy D, Goldfarb D, Intorcia D, Olgin J, Clark K, King K, York K, Reade M, Callan M, Glass M, Johnson M, Gutierrez M, Goddard M, Trncic N, Choudhury P, Reyes P, Lowery S, Hall S, Olgin S, de Santiago S, Alosco M, Ton A, Jimenez A, Ellison A, Tran A, Anderson B, Carter D, Veronelli D, Lenio S, Steinberg E, Mez J, Weller J, Johns J, Mez J, Harkins J, Puleio A, Hoti I, Mwicigi J, Puleio A, Alosco M, Schultz O, Lauture M, Steinberg E, Denis R, Killiany R, Singh S, Lenio S, Qiu W, Devis Y, Obisesan T, Stone A, Ordor D, Udodong I, Okonkwo I, Khan J, Turner J, Hughes K, Kadiri O, Duffy C, Moss A, Stapleton K, Toth M, Sanders M, Ayres M, Hamski M, Fatica P, Ogrocki P, Ash S, Pot S, Chen D, Soto A, Tanase C, Bissig D, Vanya H, Russell H, Patel H, Zhang H, Wallace K, Ayers K, Gallegos M, Forloines M, Sinn M, Kahulugan Q, Isip R, Calderon S, Hamm T, Borrie M, Lee T, Bartha R, Johnson S, Asthana S, Carlsson C, Perrin A, Tariot P, Fleisher A, Reeder S, Capote H, Emborsky A, Mattle A, Ajtai B, Benjamin Wagner C, Myers B, Slazyk D, Delaney Fragale C, Fransen E, Macnamara H, Jonathan Falletta C, Hirtreiter J, Mechtler L, King M, Asbach M, Rainka M, Zawislak R, Wisniewski S, Stephanie O'Malley C, Jimenez-Knight T, Peehler T, Aladeen T, Bates V, Wenner V, Elmalik W, Scharre D, Ramamurthy A, Bouchachi S, Kataki M, Tarawneh R, Kelley B, Celmins D, Leader A, Figueroa C, Bauerle H, Patterson K, Reposa M, Presto S, Ahmed T, Stewart W, Pearlson G, Blank K, Anderson K, Santulli R, Schwartz E, Williamson J, Jessup A, Williams A, Duncan C, O'Connell A, Gagnon K, Zamora E, Bateman J, Crawford F, Thompson D, Walker E, Rowell J, White M, Ledford P, Bohlman S, Henkle S, Bottoms J, Moretz L, Hoover B, Shannon M, Samantha Rogers C, Baker W, Harrison W, Wu C, DeMarco A, Stipanovich A, Arcuri D, Clark J, Davis J, Doyon K, Amoyaw M, Acosta M, Ronald Bailey R, Warren S, Fogerty T, Sanborn V, Riddle M, Salloway S, Malloy P, Correia S, Windon C, Blackburn M, Rosen H, Miller B, Smith A, Mba I, Echevarria J, Janavs J, Roglaski E, Yong M, Devine R, Okhravi H, Rivera E, Kalowsky T, Smith C, Rosario C, Masdeu J, Le R, Gurung M, Sabbagh M, Garcia A, Slaughter M, Elayan N, Acothley S, Pomara N, Hernando R, Pomara V, Reichert C, Brawman-Mintzer O, Acree A, Williams A, Long C, Long R, Newhouse P, Hill S, Boegel A, Seshadri S, Saklad A, Jones F, Hu W, Sotelo V, Rojas Y, Mintzer J, Longmire C, Spicer K, Barkhof F, Benke T, Chen C, Dal-Bianco P, Dewenter A, Duering M, Enzinger C, Ewers M, Exalto L, Fletcher E, Franzmeier N, Hilal S, Hofer E, Koek H, Maier A, Maillard P, McCreary C, Papma J, Pijnenburg Y, Schmidt R, Smith E, Steketee R, van den Berg E, van der Flier W, Venkatraghavan V, Venketasubramanian N, Vernooij M, Wolters F, Xu X, Horn A, Patil K, Eickhoff S, Thomalla G, Biesbroek J, Biessels G, Cheng B. Enhancing cognitive performance prediction by white matter hyperintensity connectivity assessment. Brain 2024, 147: 4265-4279. PMID: 39400198, PMCID: PMC11629703, DOI: 10.1093/brain/awae315.Peer-Reviewed Original ResearchLesion network mappingCognitive performanceCognitive domainsBrain networksWhite matter regionsCognitive disordersCognitive impairmentExtent of cognitive deficitsWMH volumeAssociated with lower cognitive performanceVentral attention networkPredicting cognitive performanceAssociated with cognitive impairmentCurrent cognitive performancePredicting cognitive functionMatter regionsBrain network connectivityLower cognitive performanceMemory clinic patientsCognitive deficitsLanguage functionBrain regionsRisk of cognitive disordersCognitive functionWhite matter hyperintensitiesBayesian pathway analysis over brain network mediators for survival data
Tian X, Li F, Shen L, Esserman D, Zhao Y. Bayesian pathway analysis over brain network mediators for survival data. Biometrics 2024, 80: ujae132. PMID: 39530270, PMCID: PMC11555425, DOI: 10.1093/biomtc/ujae132.Peer-Reviewed Original ResearchConceptsAccelerated failure time modelFailure time modelBrain connectivityAlzheimer's Disease Neuroimaging Initiative studyMaximum information extractionResponse regressionBayesian approachInformation extractionTime modelSurvival dataNoisy componentsUnique edgeWhite matter fiber tractsNetwork configurationBrain networksInterconnection networksNetworkNetwork mediatorsBrainExploring nonlinear dynamics in brain functionality through phase portraits and fuzzy recurrence plots
Li Q, Calhoun V, Pham T, Iraji A. Exploring nonlinear dynamics in brain functionality through phase portraits and fuzzy recurrence plots. Chaos An Interdisciplinary Journal Of Nonlinear Science 2024, 34: 103123. PMID: 39393183, DOI: 10.1063/5.0203926.Peer-Reviewed Original ResearchConceptsFuzzy recurrence plotsPhase portraitsComplex brain networksConnectivity descriptorsLow-dimensional dynamicsField of statistical physicsNonlinear dynamicsNeural mass modelMass modelRecurrence plotsStatistical physicsNeural time seriesFunctional connectivityLimit cycle attractorNonlinear phenomenaHidden informationComplex networksLatent informationPhase trajectoriesHigh-dimensionalDynamical theoryBrain functional connectivityBrain connectivityBrain networksNeural dynamicsA shared spatial topography links the functional connectome correlates of cocaine use disorder and dopamine D2/3 receptor densities
Ricard J, Labache L, Segal A, Dhamala E, Cocuzza C, Jones G, Yip S, Chopra S, Holmes A. A shared spatial topography links the functional connectome correlates of cocaine use disorder and dopamine D2/3 receptor densities. Communications Biology 2024, 7: 1178. PMID: 39300138, PMCID: PMC11413242, DOI: 10.1038/s42003-024-06836-9.Peer-Reviewed Original ResearchConceptsCocaine use disorderPatterns of functional connectivityUse disorderFunctional connectivityReceptor densityLarge-scale functional brain networksMaintenance of substance useDopamine D2/3 receptorsDopamine receptor densityCortico-striatal circuitsProfile of functional connectivitySubstance use disordersFunctional brain networksNeurotransmitter receptor densityD2/3 receptorsDopamine systemTransporter bindingSubcortical systemsBrain networksSubstance useCocaineSpatial topographyDisordersDopamineBiological mechanismsEstablishing group-level brain structural connectivity incorporating anatomical knowledge under latent space modeling
Wang S, Wang Y, Xu F, Shen L, Zhao Y, Initiative A. Establishing group-level brain structural connectivity incorporating anatomical knowledge under latent space modeling. Medical Image Analysis 2024, 99: 103309. PMID: 39243600, PMCID: PMC11609031, DOI: 10.1016/j.media.2024.103309.Peer-Reviewed Original ResearchBrain structural connectivityBrain connectivityStructural connectivityBrain connectivity matricesDiffusion MRITopological propertiesGenerative network modelsWhite matter fiber tractsAttributes of nodesConnectivity estimatesBrain networksGroup-level connectivityConnectivity matrixBrain regionsConnectivity architectureKnowledge of nodesAlzheimer's diseaseLatent space modelAnatomical informationGroup-level effectsImprove biological interpretationExtensive simulationsNetwork modelABC modelAssociations 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 abnormalitiesAlcoholBrainIndividual differences in spatial working memory strategies differentially reflected in the engagement of control and default brain networks
Suljič N, Kraljič A, Rahmati M, Cho Y, Ozimič A, Murray J, Anticevic A, Repovš G. Individual differences in spatial working memory strategies differentially reflected in the engagement of control and default brain networks. Cerebral Cortex 2024, 34: bhae350. PMID: 39214852, PMCID: PMC11364466, DOI: 10.1093/cercor/bhae350.Peer-Reviewed Original ResearchConceptsCategorical representationsWorking memoryBrain activityFunctional magnetic resonance imaging studySpatial working memory strategySpatial working memory taskFrontoparietal network activitySpatial working memoryWorking memory taskEngagement of controlAssociated with distinct patternsWorking memory strategiesMagnetic resonance imaging studiesNetwork activityMemory taskBrain systemsAttentional resourcesTask trialsBrain networksMemory strategiesStimulus informationStronger deactivationTiming of stimuliHealthy participantsSpatial representationPower and reproducibility in the external validation of brain-phenotype predictions
Rosenblatt M, Tejavibulya L, Sun H, Camp C, Khaitova M, Adkinson B, Jiang R, Westwater M, Noble S, Scheinost D. Power and reproducibility in the external validation of brain-phenotype predictions. Nature Human Behaviour 2024, 8: 2018-2033. PMID: 39085406, DOI: 10.1038/s41562-024-01931-7.Peer-Reviewed Original ResearchHuman Connectome ProjectAdolescent Brain Cognitive Development StudyConnectome ProjectCognitive Development StudyPhiladelphia Neurodevelopmental CohortHealthy Brain NetworkStructural connectivity dataMatrix reasoningWorking memoryAnxiety/depression symptomsAttention problemsNeurodevelopmental CohortBrain networksBrain-phenotype associationsEffect sizeConnectivity dataExternal validationRelated processesValidation studySample sizeBrain ProjectDevelopment studiesTraining sample sizeGeneralizability of modelsExternal samples4D 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 networks
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