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. 2020 Aug 11;63(1):e72. doi: 10.1192/j.eurpsy.2020.73

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© The Author(s) 2020

This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Figure 2. — Sparse canonical correlation analysis (sCCA) for language features and resting-state network functional connectivity in the entire study sample. (A) sCCA of linguistic features and resting-state network functional connectivity in the entire sample identified a single significant mode. The weight of diagnosis was −0.03; (B) linguistic features with the highest absolute weights; and (C) connectivity measures with the highest absolute weights. Additional information in Supplementary Tables S9 and S10.