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. 2024 Apr 17;629(8011):393–401. doi: 10.1038/s41586-024-07309-z

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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 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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Extended Data Fig. 1 — (a-e) Spike-sorting quality metrics. (a) Proportion of inter-spike intervals (ISI) below 3 ms. (b) Average firing rate. (c) Coefficient-of-variation. (d) Signal-to-noise ratio (SNR) for the peak of the mean waveform across all spikes as compared to the standard deviation of the background noise. (e) Mean SNR of the waveform. (f) Example raw LFP recorded in a hippocampal channel during the delay period of a single trial (time 0 denotes onset of the delay period). (g) Power-spectrum of LFP data shown in (f). (h,i) Wavelet characteristics for all 40 wavelets used. Left: Wavelet family. The upper panel shows the temporal outline and the magnitude of the real part for all wavelets smoothed across all frequencies. The maximal magnitude of each wavelet is scaled to 1. Warm colours denote positive, cold colours negative magnitude. The lower panel shows the real part of all wavelets plotted on top of each other. Centre: The upper panel shows the spectral bandwidth of each wavelet as a function of centre frequency. The lower panel plots the FFT-spectrum for each wavelet. Right: The upper panel shows the temporal width of all wavelets as a function of centre frequency. The horizontal lines indicate the spectral bandwidth for each wavelet. The lower panel contains the amplitude envelope for each wavelet as a function of time. (j) Example original and reconstructed signal after applying the continuous wavelet transform (see Methods). Small deviations from the original signal are due to the fact that signals at frequencies lower or higher than the edge frequencies of 2 and 150 Hz, respectively, were not represented by the wavelet transform but present in the original signal. (k) Assessment of the wavelet-based signal reconstruction. We computed linear models using the reconstructed signal as predictor for the original signal and extracted R-squared values as a function of time and frequency in each trial and channel. Values were averaged across all trials and all hippocampal channels. An R-squared values of close to 1 indicates almost perfect reconstruction of the original signal. As stated above, the slight drop in reconstruction quality at extreme frequencies is explained by the fact that signals at frequencies lower or higher than the edge frequencies, respectively, were not represented by the wavelet transform but present in the original signal.