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. 2024 Jan 27;15:808. doi: 10.1038/s41467-024-45105-5

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© The Author(s) 2024

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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Fig. 2 — a Neuronal reliability of a RGC to the same image dimension (256 ×256 pixels) or to different image dimensions (256 x 256 pixels vs 128 ×128 pixels). The scatter plots are built from the response vectors. The red and green dots correspond to the red and green numbers in the response vectors. The gray lines are the identity lines. b Plots of the paired neuronal reliabilities for all the recorded RGCs (n = 12 RGCs from N = 3 retinas). c, Each boxplot is the distribution of the pairwise difference in neuronal reliability from panel b. The box spans from 25^th to the 75^th percentiles, the line is the median, and the whiskers are 1.5 times the interquartile range. The black dots indicate outliers. Two-tailed paired Wilcoxon tests: 256 − 128 (p = 0.30, reported as n.s.), 256 − 64 (p = 0.0122, reported as *), 256 − 32 (p = 0.0005, reported as ***), 128 − 64 (p = 0.0200, reported as *), 128 − 32 (p = 0.0005, reported as ***), 64 − 32 (p = 0.0009, reported as ***). Statistical analysis applies to both panels b and c. High-resolution image reproduced from the Open Access van Hateren Natural Image Dataset available at https://github.com/hunse/vanhateren (MIT License).