Affiliation:
1. 1FB KMUB, Technische Hochschule Mittelhessen (THM), Wiesenstr. 14, 35390 Giessen, Germany
Abstract
AbstractWhen recording action potentials (spikes) from many neurons simultaneously via multichannel micro-electrodes the overlapping of spikes from different neurons is a demanding problem for detection and classifi-cation of spikes (spike sorting). Since multichannel electrodes provide better possibilities to separate the superimposed waveforms, we refined an algorithm for separation of overlapping spikes for the use on multichannel recordings and tested it on simulated data with different numbers of signal channels and with several signal parameters. We show that the larger the number of signal channels the better the separation that may be achieved, especially under demanding recording conditions.
Reference16 articles.
1. Bayesian modeling and classification of neural signals;Neural Comput,1994
2. A model-based spike sorting algorithm for removing correlation artifacts in multi-neuron recordings;PloS one,2013
3. Are heptodes better than tetrodes for spike sorting?;9th IFAC Symposium on Biological and Medical Systems,2015
4. The multitrode-effect influences the spike sorting performance: a simulation study;Biomed Tech,2014
5. Spike sorting: The first step in decoding the brain: The first step in decoding the brain;In: IEEE Signal Process. Mag,2012
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