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. 2019 Apr 15;9:6033. doi: 10.1038/s41598-019-42429-x

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© The Author(s) 2019

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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Temporal generalization. (A,B) Generalization of image decoding across time for high and low memorable images. The trained SVM classifier on MEG data at a given time point t (training time) was tested on data at all other time points t’ (testing time). The resulting decoding matrices were averaged within high or low memorable scene images and over all subjects. White contour indicates significant decoding values. Statistical tests used a cluster-size permutation procedure using cluster defining threshold P < 0.05, and corrected significance level P < 0.05 (n = 15).