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. 2020 Jun 9;11:493. doi: 10.3389/fneur.2020.00493

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Copyright © 2020 Gogeascoechea, Kuck, van Asseldonk, Negro, Buitenweg, Yavuz and Sartori.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Example of quality control procedure. (A) α-MN spike trains and (B) discharge rates of a α-MN pool before quality control. The algorithm rejects the α-MN with PNR <20 dB. In this case, as the cross-correlation improved by filtering the α-MNs with a coefficient of variation of the inter-spike intervals >0.3, the algorithm removes them as well. (C) Comparison between force (gray line) and the smoothed CST before (blue) and after (red) quality control. For illustrative purposes, the smoothed CST is scaled to the maximum value of the force and shifted to compensate for the neuro-mechanical delay (~0.6 s). Although some spike trains were removed after quality control, the correlation between force and smoothed CST improved. CST, cumulative spike train; pps, pulses per second.