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ICA
2010
Springer

Decomposition of EEG Signals for Multichannel Neural Activity Analysis in Animal Experiments

13 years 11 months ago
Decomposition of EEG Signals for Multichannel Neural Activity Analysis in Animal Experiments
We describe in this paper an advanced protocol for the discrimination and the classification of neuronal spike waveforms within multichannel electrophysiological recordings. Sparse decomposition was used to serarate the linearly independent signals underlying sensory information in cortical spike firing patterns. We introduce some modifications in the the IDE algorithm to take into account prior knowledge on the spike waveforms. We have investigated motor cortex responses recorded during movement in freely moving rats to provide evidence for the relationship between these patterns and special behavioral task. Key words: Sparse decomposition, classification, semi-supervised learning, Atomic Decomposition, neuronal spikes detection
Vincent Vigneron, Hsin Chen, Yen-Tai Chen, Hsin-Yi
Added 07 Dec 2010
Updated 07 Dec 2010
Type Conference
Year 2010
Where ICA
Authors Vincent Vigneron, Hsin Chen, Yen-Tai Chen, Hsin-Yi Lai, You-Yin Chen
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