Algorithms of Classification of Neuron Impulses Based on Dynamic Equations

Olga K. Chibirova; Steve Larouche; Alesandro E. P. Villa; Tatyana I. Aksenova

doi:10.1615/J Automat Inf Scien.v37.i2.60

Journal of Automation and Information Sciences

Editor-in-Chief: Arkadiy A. Chikriy (open in a new tab)

Associate Editors: Vyacheslav F. Gubarev (open in a new tab) Yuriy P. Kondratenko (open in a new tab) Nonna V. Turovyerova (open in a new tab)

Published 12 issues per year

ISSN Print: 1064-2315

ISSN Online: 2163-9337

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Algorithms of Classification of Neuron Impulses Based on Dynamic Equations

Volume 37, Issue 2, 2005, pp. 46-54

DOI: 10.1615/J Automat Inf Scien.v37.i2.60

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Olga K. Chibirova
Joseph Fourier University, Grenoble, France

Steve Larouche
Sherbrooke University, Canada

Alesandro E. P. Villa
Joseph Fourier University, Grenoble, France

Tatyana I. Aksenova
Zhozef Fourier University, Grenoble, France

ABSTRACT

A description of computer implementation of an algorithm for classification of neuron impulses (ACNI) using nonlinear dynamic equations is given. ACNI includes an automated learning procedure and allows a real-time classification of impulses of several neurons, recorded by a single microelectrode. Results of algorithm testing on a simulated signal with different noise levels are presented. We also demonstrate applications of ACNI for studying of neuron activity in the subthalamic kernel of brain, which is the goal zone for high-frequency electric stimulation of depth zones of brain in Parkinson's disease.

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