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. 2021 Oct 19;5(10):e24208. doi: 10.2196/24208

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©Jeremy L Smith, Jason W Allen, Carla I Haack, Kathryn L Wehrmeyer, Kayley G Alden, Maha B Lund, Jennifer S Mascaro. Originally published in JMIR Formative Research (https://formative.jmir.org), 19.10.2021.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.

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Results of principal components decomposition of Δconn matrix. (a) explained variance and cumulative explained variance for the first 14 principal axes. 13 components accounted for 99.99% of the explained variance in the delta matrix (Δconn), suggesting a large amount of multicollinearity across ROI-ROI connections. The recomposition of the Δconn matrix from the 13 selected components is shown in the inset. (b) within-group correlations between per-subject Δconn values and the 13 selected components, averaged across subjects within each group. (c) Primary contributors to each component based on the dot product of the original Δconn matrix and the 13-PC decomposition. Note the substantive contributions of posterior superior temporal, fusiform (t14), orbitofrontal, and default mode, dorsal attention, and salience-network components to components PC1 and PC2. These two components represented nearly one-third of the explained variance in the Δconn matrix. DAN: dorsal attention network; DMN: default mode network; PFC: prefrontal cortex; SN: salience network; STG: superior temporal gyrus.