High performers demonstrate greater neural synchrony than low performers across behavioral domains
Chamberlain T, Corriveau A, Song H, Kwon Y, Yoo K, Chun M, Rosenberg M. High performers demonstrate greater neural synchrony than low performers across behavioral domains. Imaging Neuroscience 2024, 2: 1-17. DOI: 10.1162/imag_a_00128.Peer-Reviewed Original ResearchBrain-behavior relationshipsBrain activityBehavioral domainsIntersubject representational similarity analysisPatterns of brain activityRepresentational similarity analysisBehavior scoresNeural similarityBehavior ScaleParticipant sampleNeural synchronyBehavioral similaritiesFMRI datasetsBrainSimilarity analysisLow performanceIndividualsScoresScorersBehaviorTheoretical frameworkParticipantsRelationshipTacit assumptionSynchronyEdge-Based General Linear Models Capture Moment-to-Moment Fluctuations in Attention
Jones H, Yoo K, Chun M, Rosenberg M. Edge-Based General Linear Models Capture Moment-to-Moment Fluctuations in Attention. Journal Of Neuroscience 2024, 44: e1543232024. PMID: 38316565, PMCID: PMC10993033, DOI: 10.1523/jneurosci.1543-23.2024.Peer-Reviewed Original ResearchMoment-to-moment fluctuationsFMRI functional connectivityFMRI analysisProcessing of task-relevant informationSustained attention taskTask-based fMRITask-relevant informationDynamic FC approachParametric fMRI analysisField of network neuroscienceTraditional fMRI analysisNeural underpinningsAttention taskSustained attentionIndividual differencesCognitive processesTask eventsFunctional connectivityNetwork neuroscienceRegions-of-interestGeneralized linear modelAttentional stateFMRI datasetsYoung adultsIndividual's ability