On-Line Real-Time Oriented Application for Neuronal Spike Sorting with Unsupervised Learning.

Details

Serval ID
serval:BIB_36139
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Institution
Title
On-Line Real-Time Oriented Application for Neuronal Spike Sorting with Unsupervised Learning.
Title of the conference
Artificial Neural Networks: Biological Inspirations – ICANN 2005: 15th International Conference, Warsaw, Poland, September 11-15, 2005. Proceedings, Part I
Author(s)
Asai Y., Aksenova T.I., Villa A.E.P.
Publisher
Springer
Address
Warsaw, Poland
ISBN
978-3-540-28754-4
978-3-540-28752-0
Publication state
Published
Issued date
2005
Peer-reviewed
Oui
Editor
Duch W., Kacprzyk J., Oja E., Zadrożny S.
Volume
3696
Series
Lecture Notes in Computer Science
Pages
109-114
Language
english
Abstract
Multisite electrophysiological recordings have become a standard tool for exploring brain functions. These techniques point out the necessity of fast and reliable unsupervised spike sorting. We present an algorithm that performs on-line real-time spike sorting for data streaming from a data acquisition board or in off-line mode from a WAV formatted file. Spike shapes are represented in a phase space according to the first and second derivatives of the signal trace. The output of the application is spike data format file in which the timing of spike occurrences are recorded by their inter-spike-intervals. It allows its application to the study of neuronal activity patterns in clinically recorded data.
Web of science
Create date
19/11/2007 10:10
Last modification date
20/08/2019 13:23
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