Characterizing spike trains with Lempel-Ziv complexity

被引：0
|
作者：
Szczepanski, J
Amigó, JM
Wajnryb, E
Sanchez-Vives, A
机构：
[1] Univ Miguel Hernandez, Ctr Invest Operat, Elche 03202, Spain
[2] PAS, Inst Fundamental Technol Res, Warsaw, Poland
[3] Univ Miguel Hernandez, Inst Neurosci, CSIC, Alicante 03350, Spain
来源：
NEUROCOMPUTING | 2004年 / 58卷
关键词：
lempel-ziv complexity; entropy; spike trains; neuronal sources;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We review several applications of Lempel-Ziv complexity to the characterization of neural responses. In particular, Lempel-Ziv complexity allows to estimate the entropy of binned spike trains in an alternative way to the usual method based on the relative frequencies of words, with the definitive advantage of no requiring very long registers. We also use complexity to discriminate neural responses to different kinds of stimuli and to evaluate the number of states of neuronal sources. (C) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码：79 / 84
页数：6
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