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. 2020 Nov 10;9:e61834. doi: 10.7554/eLife.61834

Figure 2. Evaluation of spike sorters on a simulated Neuropixels dataset.

(A) A visualization of the activity on and traces from the simulated Neuropixels recording. (B) The signal-to-noise ratios (SNR) for the ground-truth units. (C) The number of detected units for each of the six spike sorters (HS = HerdingSpikes2, KS = Kilosort2, IC = IronClust, TDC = Tridesclous, SC = SpyKING Circus, HDS = HDSort). (D) The accuracy, precision, and recall of each sorter on the ground-truth units. (E) A breakdown of the detected units for each sorter (precise definitions of each unit type can be found in the SpikeComparison Section of the Methods). The horizontal dashed line indicates the number of ground-truth units (250).

Figure 2.

Figure 2—figure supplement 1. Evaluation of spike sorters performance metrics.

Figure 2—figure supplement 1.

(A) Precision versus recall for the ground-truth comparison the simulated dataset. Some sorters seem to favor precision (HerdingSpikes, SpyKING Circus, HDSort), others instead have higher recall (Ironclust) or score well on both measures (Kilosort2). Tridesclous does not show a bias towards precision or recall. (B) Accuracy versus SNR. All the spike sorters (except Kilosort2) show a strong dependence of performance with respect to the SNR of the ground-truth units. Kilosort2, remarkably, is capable of achieving a high accuracy also for low-SNR units.