Identification of reliable spike templates in multi-unit extracellular recordings using fuzzy clustering

A method for extracting single-unit spike trains from extracellular recordi ngs containing the activity of several simultaneously active cells is prese nted. The technique is particularly effective when spikes overlap temporall y. It is capable of identifying the exact number of neurons contributing to a recording and of creating reliable spike templates. The procedure is bas ed on fuzzy clustering and its performance is controlled by minimizing a cl uster-validity index which optimizes the compactness and separation of the identified clusters. Application examples with synthetic spike trains gener ated from real spikes and segments of background noise show the advantage o f the fuzzy method over conventional template-creation approaches in a wide range of signal-to-noise ratios. (C) 2000 Elsevier Science Ireland Ltd. Al l rights reserved.