A NEURAL-NETWORK-BASED SPIKE DISCRIMINATOR

被引：15

作者：

OGHALAI, JS ^{[1
]}

STREET, WN ^{[1
]}

RHODE, WS ^{[1
]}

机构：

[1] UNIV WISCONSIN, DEPT COMP SCI, MADISON, WI 53706 USA

来源：

JOURNAL OF NEUROSCIENCE METHODS | 1994年 / 54卷 / 01期

关键词：

MULTIUNIT SPIKE TRAIN; SPIKE DISCRIMINATION; EXTRACELLULAR RECORDING; COCHLEAR NUCLEUS; NEURAL NETWORK; ART-2;

D O I：

10.1016/0165-0270(94)90155-4

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

A software routine to reconstruct individual spike trains from multi-neuron, single-channel extracellular recordings was designed. Using a neural network algorithm that automatically clusters and sorts the spikes, the only user input needed is the threshold level for spike detection and the number of unit types present in the recording. Adaptive features are included in the algorithm to allow for tracking of spike trains during periods of amplitude variation and also to identify noise spikes. The routine will operate on-line during extracellular studies of the cochlear nucleus in cats.

引用

页码：9 / 22

页数：14

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