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. 2019 Aug 30;9(7):566–579. doi: 10.1089/brain.2019.0673

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Copyright 2019, Mary Ann Liebert, Inc., publishers

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FIG. 1. — Illustrated representation of the decomposition process of sDL. A matrix representing the complete volume of v voxel signals acquired from a scan of time t is arranged into a signal matrix . Through sDL, the matrix is decomposed into a dictionary matrix and , such that approximates . Dictionary contains activity for n number of atoms, or detected RSNs, whereas contains representations of the detect RSN maps that can be mapped back to a brain volume. BOLD, blood-oxygenation-level dependent; fMRI, functional magnetic resonance imaging; RSNs, resting-state networks; sDL, sparse dictionary learning.

Inline graphic — Illustrated representation of the decomposition process of sDL. A matrix representing the complete volume of v voxel signals acquired from a scan of time t is arranged into a signal matrix . Through sDL, the matrix is decomposed into a dictionary matrix and , such that approximates . Dictionary contains activity for n number of atoms, or detected RSNs, whereas contains representations of the detect RSN maps that can be mapped back to a brain volume. BOLD, blood-oxygenation-level dependent; fMRI, functional magnetic resonance imaging; RSNs, resting-state networks; sDL, sparse dictionary learning.