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

被引：51

作者：

Zouridakis, G

Tam, DC

机构：

[1] Univ Texas, Sch Med, Dept Neurosurg, Houston, TX 77030 USA

[2] Univ N Texas, Dept Biol Sci, Denton, TX 76203 USA

来源：

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE | 2000年 / 61卷 / 02期

关键词：

multi-unit spike train; template extraction; spike discrimination; fuzzy clustering; fuzzy K-means;

D O I：

10.1016/S0169-2607(99)00032-2

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A method for extracting single-unit spike trains from extracellular recordings containing the activity of several simultaneously active cells is presented. The technique is particularly effective when spikes overlap temporally. It is capable of identifying the exact number of neurons contributing to a recording and of creating reliable spike templates. The procedure is based on fuzzy clustering and its performance is controlled by minimizing a cluster-validity index which optimizes the compactness and separation of the identified clusters. Application examples with synthetic spike trains generated from real spikes and segments of background noise show the advantage of the fuzzy method over conventional template-creation approaches in a wide range of signal-to-noise ratios. (C) 2000 Elsevier Science Ireland Ltd. All rights reserved.

引用

页码：91 / 98

页数：8

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