Title
On-Line real-time oriented application for neuronal spike sorting with unsupervised learning
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.
Year
DOI
Venue
2005
10.1007/11550822_18
ICANN (1)
Keywords
Field
DocType
on-line real-time spike,neuronal activity pattern,spike data format file,neuronal spike,brain function,wav formatted file,on-line real-time oriented application,multisite electrophysiological recording,reliable unsupervised spike,unsupervised learning,data acquisition board,spike occurrence,spike shape,neuronal activity,phase space,real time,data acquisition
File format,Signal processing,Signal trace,Spike sorting,Pattern recognition,Computer science,Data acquisition,Speech recognition,Unsupervised learning,Artificial intelligence,Electrophysiology,Data flow diagram
Conference
Volume
ISSN
ISBN
3696
0302-9743
3-540-28752-3
Citations 
PageRank 
References 
1
0.39
2
Authors
3
Name
Order
Citations
PageRank
Yoshiyuki Asai1307.56
Tetyana I. Aksenova211.06
Alessandro E . P. Villa334853.26