Abstract
We describe in this paper some advanced protocols for the discrimination and 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 pat- terns. 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 ev- idence for the relationship between these patterns and special behavioral task.
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Vigneron, V., Chen, H., Chen, YT., Lai, HY., Chen, YY. (2010). Decomposition of EEG Signals for Multichannel Neural Activity Analysis in Animal Experiments. In: Vigneron, V., Zarzoso, V., Moreau, E., Gribonval, R., Vincent, E. (eds) Latent Variable Analysis and Signal Separation. LVA/ICA 2010. Lecture Notes in Computer Science, vol 6365. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15995-4_59
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DOI: https://doi.org/10.1007/978-3-642-15995-4_59
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