抄録
Recently, experimental studies for activities of multi-neurons have been significantly increased because of advanced technologies of extracellular recordings with multi channel linear-probe or calcium imaging with two-photon microscopy. Therefore the sizes of experimental data have been also increased with the development of the experimental technique. However, the method that extracts the spike trains of multiple neurons from raw data have not yet established. In this study, we introduce an improved spike-sorting framework using a novel signal detection and a clustering method. We also introduce a cell-sorting framework using the sparseness of cell sizes and spike firing.
