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Title: Bayes optimal template matching for spike sorting - combining fisher discriminant analysis with optimal filtering
Authors: Franke, F.
Quian Quiroga, Rodrigo
Hierlemann, A.
Obermayer, K.
First Published: 5-Feb-2015
Publisher: Springer Verlag (Germany)
Citation: Journal of Computational Neuroscience, 2015, 38 (3), pp. 439-459
Abstract: Spike sorting, i.e., the separation of the firing activity of different neurons from extracellular measurements, is a crucial but often error-prone step in the analysis of neuronal responses. Usually, three different problems have to be solved: the detection of spikes in the extracellular recordings, the estimation of the number of neurons and their prototypical (template) spike waveforms, and the assignment of individual spikes to those putative neurons. If the template spike waveforms are known, template matching can be used to solve the detection and classification problem. Here, we show that for the colored Gaussian noise case the optimal template matching is given by a form of linear filtering, which can be derived via linear discriminant analysis. This provides a Bayesian interpretation for the well-known matched filter output. Moreover, with this approach it is possible to compute a spike detection threshold analytically. The method can be implemented by a linear filter bank derived from the templates, and can be used for online spike sorting of multielectrode recordings. It may also be applicable to detection and classification problems of transient signals in general. Its application significantly decreases the error rate on two publicly available spike-sorting benchmark data sets in comparison to state-of-the-art template matching procedures. Finally, we explore the possibility to resolve overlapping spikes using the template matching outputs and show that they can be resolved with high accuracy.
DOI Link: 10.1007/s10827-015-0547-7
ISSN: 0929-5313
eISSN: 1573-6873
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright The Author(s) 2015. This article is published with open access at This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
Appears in Collections:Published Articles, Dept. of Engineering

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