A modulated template-matching approach to improve spike sorting of bursting neurons
| Autor: | Payam S. Shabestari, Alessio P. Buccino, Sreedhar S. Kumar, Alessandra Pedrocchi, Andreas Hierlemann |
|---|---|
| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | 2021 IEEE Biomedical Circuits and Systems Conference (BioCAS) IEEE Biomed Circuits Syst Conf |
| DOI: | 10.1109/biocas49922.2021.9644995 |
| Popis: | In extracellular neural electrophysiology, individual spikes have to be assigned to their cell of origin in a procedure called “spike sorting”. Spike sorting is an unsupervised problem, since no ground-truth information is generally available. Here, we focus on improving spike sorting performance, particularly during periods of high synchronous activity or so-called “bursting”. Bursting entails systematic changes in spike shapes and amplitudes and remains a challenge for current spike sorting schemes. We use realistic simulated bursting recordings of high-density micro-electrode arrays (HD-MEAs) and we present a fully automated algorithm based on template matching with a focus on recovering missed spikes during bursts. To compare and benchmark spike-sorting performance after applying our method, we used ground-truth information of simulated recordings. We show that our approach can be effective in improving spike sorting performance during bursting. Further validation with experimental recordings is necessary. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|