2017
Hierarchical Organization of Tau and Amyloid Deposits in the Cerebral Cortex
Sepulcre J, Grothe M, Sabuncu M, Chhatwal J, Schultz A, Hanseeuw B, Fakhri G, Sperling R, Johnson K. Hierarchical Organization of Tau and Amyloid Deposits in the Cerebral Cortex. JAMA Neurology 2017, 74: 813-820. PMID: 28558094, PMCID: PMC5710537, DOI: 10.1001/jamaneurol.2017.0263.Peer-Reviewed Original ResearchConceptsHeteromodal areasTemporal lobeHarvard Aging Brain StudyHeteromodal association regionsAging Brain StudyCognitively normal participantsElderly brainsPositron emission tomographicPrimary somatomotor cortexDistribution volume ratioAlzheimer's diseaseTau depositionStandardized uptake value ratioVisual regionsNormal participantsAb depositionSomatomotor cortexTemporal areaPittsburgh compound BCarbon 11-labeled Pittsburgh Compound BBrain studiesAssociation regionsHuman brainPathological hallmarks of Alzheimer's diseaseCortical distribution
2013
Matched Signal Detection on Graphs: Theory and Application to Brain Network Classification
Hu C, Cheng L, Sepulcre J, El Fakhri G, Lu Y, Li Q. Matched Signal Detection on Graphs: Theory and Application to Brain Network Classification. Lecture Notes In Computer Science 2013, 23: 1-12. PMID: 24683953, DOI: 10.1007/978-3-642-38868-2_1.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAlzheimer DiseaseAniline CompoundsBenzothiazolesBrainBrain MappingConnectomeHumansImage EnhancementImage Interpretation, Computer-AssistedNerve NetNeural PathwaysPattern Recognition, AutomatedPositron-Emission TomographyReproducibility of ResultsSensitivity and SpecificityThiazolesTissue DistributionConceptsBrain network classificationNetwork classification problemWeighted energy detectorPrinciple component analysisSub-manifold structureTraditional principle component analysisSubspace detectionTraining dataEnergy detectorGraph structureProblem of Alzheimer's diseaseGraph LaplacianNetwork classificationNoise varianceLevel of smoothnessWeighted graphSignal detectionIntrinsic structureSignal modelGraphSubspaceIsing modelNoiseSignal variationsComponent analysis