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. 2023 May 24;13:8418. doi: 10.1038/s41598-023-35179-4

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Early changes in the delta and alpha relative power bands predict improvement in depressive symptoms. (A,C) The plots depict the ROC curve across all possible threshold values of the predictor for average power relative value within the clusters found in the delta band (A), and in the alpha band (C) at the sensor space. (B,D) The plots depict the ROC curve across all possible threshold values of the predictor for average power relative value in the delta band (B) and the alpha band (D) across regions found significant at the source space. (A–D) In all plots, x-axes represent false positive rates (1-specificity), y-axes the true positive values (sensitivity). Here, specificity corresponds to the percentage of non-responders who were predicted to be non-responders, and sensitivity corresponds to the percentage of responders who were predicted to be responders. The red circle shows the optimum operating point of the ROC curve.