Combining Multiple Behavioral Measures and Multiple Connectomes via Multipath Canonical Correlation Analysis
Gao S, Shen X, Todd Constable R, Scheinost D. Combining Multiple Behavioral Measures and Multiple Connectomes via Multipath Canonical Correlation Analysis. Lecture Notes In Computer Science 2019, 11766: 772-780. DOI: 10.1007/978-3-030-32248-9_86.Peer-Reviewed Original ResearchCombining multiple connectomes improves predictive modeling of phenotypic measures
Gao S, Greene AS, Constable RT, Scheinost D. Combining multiple connectomes improves predictive modeling of phenotypic measures. NeuroImage 2019, 201: 116038. PMID: 31336188, PMCID: PMC6765422, DOI: 10.1016/j.neuroimage.2019.116038.Peer-Reviewed Original ResearchConceptsMultiple connectomesLarge open-source datasetOpen-source datasetNovel prediction frameworkPredictive modelingSingle predictive modelPredictive modelArt algorithmsPrediction frameworkMultiple tasksPredictive model approachPrincipled waySpecific algorithmsFunctional connectivity matricesConnectivity matrixDifferent tasksPrediction performanceConnectome-based predictive modelingHuman Connectome ProjectTaskSuperior performanceAlgorithmComplementary informationNaïve extensionsConnectome Project