2022
Local Functional Connectivity as a Parsimonious Explanation of the Main Frameworks for ADHD in Medication-Naïve Adults
Marcos-Vidal L, Martínez-García M, Blas D, Navas-Sánchez F, Pretus C, Ramos-Quiroga J, Richarte V, Vilarroya Ó, Sepulcre J, Desco M, Carmona S. Local Functional Connectivity as a Parsimonious Explanation of the Main Frameworks for ADHD in Medication-Naïve Adults. Journal Of Attention Disorders 2022, 26: 1563-1575. PMID: 35947490, DOI: 10.1177/10870547211031998.Peer-Reviewed Original ResearchConceptsIncreased local connectivityFunctional connectivityAtypical functional connectivity patternsAssociations with symptom severity scoresDistant functional connectivityDistribution of functional connectivityLocal functional connectivityFunctional connectivity patternsDecreased local connectivityADHD sampleNeuroimaging studiesAdult samplesDeficient integrationADHDSymptom severity scoresChild sampleInterference hypothesisLocal connectivityDelay hypothesisDMNConnectivity patternsHealthy controlsDistant connectionsAdultsDistant distributionLocal Functional Connectivity as a Parsimonious Explanation of the Main Frameworks for ADHD in Medication-Naïve Adults
Marcos-Vidal L, Martínez-García M, de Blas D, Navas-Sánchez F, Pretus C, Ramos-Quiroga J, Richarte V, Vilarroya Ó, Sepulcre J, Desco M, Carmona S. Local Functional Connectivity as a Parsimonious Explanation of the Main Frameworks for ADHD in Medication-Naïve Adults. Journal Of Attention Disorders 2022, 26: 1788-1801. PMID: 35684934, DOI: 10.1177/10870547221101646.Peer-Reviewed Original ResearchConceptsIncreased local connectivityFunctional connectivityAtypical functional connectivity patternsAssociations with symptom severity scoresDistant functional connectivityDistribution of functional connectivityLocal functional connectivityFunctional connectivity patternsDecreased local connectivityADHD sampleNeuroimaging studiesAdult samplesDeficient integrationADHDSymptom severity scoresChild sampleInterference hypothesisLocal connectivityDelay hypothesisDMNConnectivity patternsHealthy controlsDistant connectionsAdultsDistant distribution
2018
Neurogenetic profiles delineate large-scale connectivity dynamics of the human brain
Diez I, Sepulcre J. Neurogenetic profiles delineate large-scale connectivity dynamics of the human brain. Nature Communications 2018, 9: 3876. PMID: 30250030, PMCID: PMC6155203, DOI: 10.1038/s41467-018-06346-3.Peer-Reviewed Original ResearchConceptsWhole-brain functional connectivityCognitive statesDepression-related genesDynamic connectivity patternsLong-term potentiationResting stateSynaptic long-term potentiationNeurobiological basisGraph theory-based analysisHeteromodal cortexFunctional connectivityPrimary sensory areasNeural activityAttention areasConnectivity patternsConnectivity dynamicsHuman brainSensory areasGenetic transcription levelsDMNTheory-based analysisDynamic connectivityDynamic streamsLocal networkTaskPositive Connectivity Predicts the Dynamic Intrinsic Topology of the Human Brain Network
Qian J, Diez I, Ortiz-Terán L, Bonadio C, Liddell T, Goñi J, Sepulcre J. Positive Connectivity Predicts the Dynamic Intrinsic Topology of the Human Brain Network. Frontiers In Systems Neuroscience 2018, 12: 38. PMID: 30214399, PMCID: PMC6125351, DOI: 10.3389/fnsys.2018.00038.Peer-Reviewed Original ResearchFunctional connectivity MRIHuman brain functional connectomeBrain functional connectomeNegative connectionFunctional connectomePositive connectionBrain network organizationStrength of negative correlationBrain areasFunctional connectivityNeuropsychiatric diseasesConnection path lengthsNeuroimaging biomarkersVoxel pairsNeuronal systemsConnectivity patternsFunctional negative correlationNegative correlationNetwork organizationCoincident interactionsPositive couplingConnectome
2015
A Spectral Graph Regression Model for Learning Brain Connectivity of Alzheimer’s Disease
Hu C, Cheng L, Sepulcre J, Johnson K, Fakhri G, Lu Y, Li Q. A Spectral Graph Regression Model for Learning Brain Connectivity of Alzheimer’s Disease. PLOS ONE 2015, 10: e0128136. PMID: 26024224, PMCID: PMC4449104, DOI: 10.1371/journal.pone.0128136.Peer-Reviewed Original ResearchConceptsNetwork featuresAlzheimer's diseaseConsistent with known pathologyUnknown graphConnection weightsReconstruction networkCortical hubsDegree statisticsData modelSmooth signalsFeatures of brain pathologyOptimization frameworkAmyloid-bPartial correlation estimationImage dataNetworkGraphGlobal connectivity measuresPositron emission tomographyConnectivity measuresNeurodegenerative diseasesConnectivity patternsSample correlationClinical ADSimulated data
2013
A GRAPH THEORETICAL REGRESSION MODEL FOR BRAIN CONNECTIVITY LEARNING OF ALZHEIMER'S DISEASE
Hu C, Cheng L, Sepulcre J, Fakhri G, Lu Y, Li Q. A GRAPH THEORETICAL REGRESSION MODEL FOR BRAIN CONNECTIVITY LEARNING OF ALZHEIMER'S DISEASE. 2013, 616-619. DOI: 10.1109/isbi.2013.6556550.Peer-Reviewed Original Research
2011
The organization of the human cerebral cortex estimated by intrinsic functional connectivity
Thomas Yeo B, Krienen F, Sepulcre J, Sabuncu M, Lashkari D, Hollinshead M, Roffman J, Smoller J, Zöllei L, Polimeni J, Fischl B, Liu H, Buckner R. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. Journal Of Neurophysiology 2011, 106: 1125-1165. PMID: 21653723, PMCID: PMC3174820, DOI: 10.1152/jn.00338.2011.Peer-Reviewed Original ResearchConceptsProperties of network connectivityMT+ complexSurface-based alignmentHierarchical relationsFunctional connectivityOrganization of networksPrimary visual areaFunctional connectivity MRIResting-state functional connectivity MRIConnectivity patternsNetwork boundariesCerebral cortexNetwork connectivityClustering approachConnectivity profilesArea complexityAnatomical connectionsLocal networkIntrinsic functional connectivityDistribution networkNetworkVisual systemVisual areasAbrupt transitionInformation processing