Extended Data Fig. 6: Timing jitters of inferred spikes relative to real spikes before and after denoising.
a, Boxplots showing the distribution of timing jitters relative to real spikes (electrophysiology) of all inferred spike pairs before (N = 2031) and after (N = 2574) denoising. b, Histograms showing the probability distributions of timing jitters before and after denoising. The two probability distributions were verified to be equivalent by Kolmogorov–Smirnov test (one-side, P ≤ 0.01, N = 2031 for raw data, N = 2574 for DeepCAD enhanced). c, Distributions of timing jitters at different input noise levels (Raw data, N = 326 for low-SNR, N = 689 for medium-SNR, N = 1016 for high-SNR; DeepCAD enhanced, N = 545 for low-SNR, N = 880 for medium-SNR, N = 1149 for high-SNR). d, Distributions of timing jitters at different baseline spike rates (Raw data, N = 663 for low spike rate, N = 766 for medium spike rate, N = 602 for high spike rate; DeepCAD enhanced, N = 1095 for low spike rate, N = 837 for medium spike rate, N = 642 for high spike rate). Baseline spike rates were calculated with 2 s binning time. All timing jitters were divided into three groups, that is low spike rate (baseline spike rate≤2.0 spk/s), medium spike rate (2.0 spk/s <baseline spike rate≤3.5 spk/s), and high baseline spike rate (baseline spike rateå 3.5 spk/s). These timing jitters were caused by the spike inference algorithm. Boxplots were plotted in standard Tukey box-and-whisker plot format with outliers indicated with small black dots.
