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. 2018 May 29;8:8357. doi: 10.1038/s41598-018-26507-0

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© The Author(s) 2018

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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Support Vector Machine classification accuracies in decoding the direction of motion (left or right) of fast-speed gratings for all visual areas (N = 4). The performance is significantly above chance (dashed line at 50%) for all areas. Shaded area shows 95% confidence intervals (C.I.).