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. 2022 Sep 15;12:15504. doi: 10.1038/s41598-022-19771-8

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© The Author(s) 2022

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

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The sorting performance of 6 spike sorting algorithms on Dataset A concerning noise levels. (a) We compared sorting accuracy of PCA-Km, LE-Km, PCA-DP, LDA-GMM, GMMsort and LDA-DP with respect to noise on the testing set C1 (noise level: 0.05, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4). Error bars represent s.e.m.. (b) DBI comparison concerning noise on the testing set C1. The evaluation was performed as in a. (c–h) Sorting accuracy and DBI concerning noise on the testing set C2, C3 and C4 respectively.