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. 2018 Nov 5;8:16310. doi: 10.1038/s41598-018-31435-0

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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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Best Performing Subject. Complete data are shown from subject G, one of the best-performing in the study. Data have been plotted according to viewing condition (P₅₀₀, P₁₀₀₀, P₂₀₀₀, P_CLEAR, or Hard, Medium, Easy, and Clear) and across font sizes (F_XS, F_S, F_M, F_L, F_XL or logMAR 1.0, 1.1, 1.2, 1.3, 1.4). The vertical axis of reading accuracy is the percent of words read correctly (upper row), and the vertical axis of reading speed is the number of words read correctly per minute (lower row). To highlight the progression of the learning process, early results are shown using traces with less saturated color, shifting to later results shown in more saturated color; data points from the first session are shown with open symbols, and data from the last session with filled. As time progresses through the 40 sessions (desaturated to colored), curves in the phosphene-view conditions move upward (or more accurately leftward as seen in Fig. 3) as the mean performance seen in the right hand column (magenta for mean over phosphene view) improves. Performance in the clear-view control condition (orange) does not show large-scale trends.