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. 2020 Apr 24;10:6922. doi: 10.1038/s41598-020-63587-3

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© The Author(s) 2020

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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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Group (left) and individual (right) Spearman correlation using only periods of high (high SpE) or low (low SpE) attention on the computation of the decoder (median ± iqr). Note that more than 80% of the group showed higher correlation using a decoder based on periods of high attention than low attention. Each dot represents the cortical speech tracking for a participant (i.e., the cortical speech tracking averaged over folds). For each fold, the cortical speech tracking is computed over a complete testing period (i.e., 4-minutes of data). This means that each Spearman correlation value is computed by comparing 61440 data points (i.e., 4 × 60 × 256) of the actual and reconstructed speech envelope. All the correlations are significant (a permutation test was used to evaluate the significance level for each model, which was at around 0.03 for each participant).