NeuroImage: Toward a connectivity gradient-based framework for reproducible biomarker discovery
December 10, 2020
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, identifying principal components of intrinsic connectivity which describe smooth transitions across different cortical systems, so called “connectivity gradients”.
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Seok-Jun Hong, PhD
Seok-Jun Hong, PhD, is a research scientist in the Center for the Developing Brain at the Child Mind Institute. Dr. … Read Bio