Connectome-based Models Predict Separable Components of Attention in Novel Individuals
Rosenberg MD, Hsu WT, Scheinost D, Constable R, Chun MM. Connectome-based Models Predict Separable Components of Attention in Novel Individuals. Journal Of Cognitive Neuroscience 2017, 30: 160-173. PMID: 29040013, DOI: 10.1162/jocn_a_01197.Peer-Reviewed Original ResearchConceptsConnectome-based predictive modelingAttention Network TaskExecutive controlIntrinsic functional organizationRT variabilityANT performanceInfluential modelFunctional connectivityBrain's intrinsic functional organizationComponents of attentionExecutive control scoresResting-state functional connectivityResting-state dataFunctional brain networksFunctional organizationTask-based dataAttentional abilitiesUpcoming stimulusExplicit taskSustained attentionFMRI scanningAttention factorNovel individualsAdditional independent componentNetwork tasks