Toward a connectivity gradient-based framework for reproducible biomarker discovery

Toward a connectivity gradient-based framework for reproducible biomarker discovery

Despite myriad demonstrations of feasibility, the high dimensionality of fMRI data remains a critical barrier to its utility for reproducible biomarker discovery. Recent efforts to address this challenge have capitalized on dimensionality reduction techniques applied to resting-state fMRI, identifyi...

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Bibliographic Details
Main Authors: Seok-Jun Hong, Ting Xu, Aki Nikolaidis, Jonathan Smallwood, Daniel S. Margulies, Boris Bernhardt, Joshua Vogelstein, Michael P. Milham
Format: Article
Language:English
Published: Elsevier 2020-12-01
Series:NeuroImage
Subjects:
Dimensionality reduction
Imaging biomarker
Reliability
Reproducibility
Phenotype prediction, CCA
Online Access:http://www.sciencedirect.com/science/article/pii/S1053811920308089

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http://www.sciencedirect.com/science/article/pii/S1053811920308089

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