2020
The Constrained Network-Based Statistic: A New Level of Inference for Neuroimaging
Noble S, Scheinost D. The Constrained Network-Based Statistic: A New Level of Inference for Neuroimaging. Lecture Notes In Computer Science 2020, 12267: 458-468. PMID: 33870336, PMCID: PMC8052680, DOI: 10.1007/978-3-030-59728-3_45.Peer-Reviewed Original ResearchNetwork-based statisticsLarge-scale networksConstrained networksLarge-scale brain networksHuman Connectome ProjectHigher effect sizesBrain networksGround truth mapConnectome ProjectTask dataTruth effectNew levelReproducible discoveryEffect sizeNBS methodTruth mapNetwork organizationNetworkLocal neighborhoodValid inferencesInferenceNeuroscienceImportant formCluster levelMajor initiatives
2017
Multimodal Investigation of Network Level Effects Using Intrinsic Functional Connectivity, Anatomical Covariance, and Structure-to-Function Correlations in Unmedicated Major Depressive Disorder
Scheinost D, Holmes SE, DellaGioia N, Schleifer C, Matuskey D, Abdallah CG, Hampson M, Krystal JH, Anticevic A, Esterlis I. Multimodal Investigation of Network Level Effects Using Intrinsic Functional Connectivity, Anatomical Covariance, and Structure-to-Function Correlations in Unmedicated Major Depressive Disorder. Neuropsychopharmacology 2017, 43: 1119-1127. PMID: 28944772, PMCID: PMC5854800, DOI: 10.1038/npp.2017.229.Peer-Reviewed Original ResearchConceptsMajor depressive disorderAnterior cingulate cortexIntrinsic functional connectivityMedial prefrontal cortexFunctional connectivityLarge-scale brain networksDepressive disorderMDD groupAnatomical covarianceBrain networksUnmedicated major depressive disorderWhole-brain intrinsic functional connectivitySystem-level disorderIntrinsic connectivity distributionRegional brain structureMultiple brain networksAltered connectivityCommon findingHealthy comparison participantsDepressive symptomsAltered volumeUnmedicated individualsLocal circuitryCingulate cortexDepressive symptomatologyCharacterizing Attention with Predictive Network Models
Rosenberg MD, Finn ES, Scheinost D, Constable RT, Chun MM. Characterizing Attention with Predictive Network Models. Trends In Cognitive Sciences 2017, 21: 290-302. PMID: 28238605, PMCID: PMC5366090, DOI: 10.1016/j.tics.2017.01.011.Peer-Reviewed Original ResearchConceptsAttention deficit hyperactivity disorderAttentional abilitiesLarge-scale brain networksLaboratory-based tasksDeficit hyperactivity disorderExplicit taskCognitive abilitiesHyperactivity disorderBrain networksBrain computationCognitive functionFunctional connectivityFunctional architectureTaskClinical dysfunctionEmpirical evidenceAttentionPredictive network modelsNeuromarkersNetwork modelAbilityRecent workNetwork propertiesDisordersPeopleMulti-modal analysis of functional connectivity and cerebral blood flow reveals shared and unique effects of propofol in large-scale brain networks
Qiu M, Scheinost D, Ramani R, Constable RT. Multi-modal analysis of functional connectivity and cerebral blood flow reveals shared and unique effects of propofol in large-scale brain networks. NeuroImage 2017, 148: 130-140. PMID: 28069540, PMCID: PMC5410383, DOI: 10.1016/j.neuroimage.2016.12.080.Peer-Reviewed Original ResearchConceptsCerebral blood flowIntrinsic connectivity distributionLarge-scale brain networksFunctional connectivityReduced consciousnessBlood flowBrain networksSedation conditionsWhole-brain connectivityAltered connectivityMotor networkCBF dataRs-fMRIPharmacological alterationsConnectivity differencesPropofolMultiple large-scale brain networksUnique neural correlatesBlow flowFrontoparietal networkAnesthesiaKey markersDefault modeNeural correlatesSame subjects