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- W4210577013 abstract "Objective. We present a framework to objectively test and compare stimulation artefact removal techniques in the context of neural spike sorting.Approach. To this end, we used realistic hybrid ground-truth spiking data, with superimposed artefacts fromin vivorecordings. We used the framework to evaluate and compare several techniques: blanking, template subtraction by averaging, linear regression, and a multi-channel Wiener filter (MWF).Main results. Our study demonstrates that blanking and template subtraction result in a poorer spike sorting performance than linear regression and MWF, while the latter two perform similarly. Finally, to validate the conclusions found from the hybrid evaluation framework, we also performed a qualitative analysis onin vivorecordings without artificial manipulations.Significance. Our framework allows direct quantification of the impact of the residual artefact on the spike sorting accuracy, thereby allowing for a more objective and more relevant comparison compared to indirect signal quality metrics that are estimated from the signal statistics. Furthermore, the availability of a ground truth in the form of single-unit spiking activity also facilitates a better estimation of such signal quality metrics." @default.
- W4210577013 created "2022-02-08" @default.
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- W4210577013 date "2022-01-25" @default.
- W4210577013 modified "2023-09-30" @default.
- W4210577013 title "Objective evaluation of stimulation artefact removal techniques in the context of neural spike sorting" @default.
- W4210577013 doi "https://doi.org/10.1088/1741-2552/ac4ecf" @default.
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