PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Modelling Spikes with Mixtures of Factor Analysers
Dilan Gorur, Carl Edward Rasmussen, Andreas S. Tolias, Fabian Sinz and Nikos K. Logothetis
Pattern Recognition Volume roc. 26th DAGM Symposium, Number LNCS 3175, pp. 391-398, 2004. ISSN 0302-9743

Abstract

Identifying the action potentials of individual neurons from extracellular recordings, known as spike sorting, is a challenging problem. We consider the spike sorting problem using a generative model,mixtures of factor analysers, which concurrently performs clustering and feature extraction. The most important advantage of this method is that it quantifies the certainty with which the spikes are classified. This can be used as a means for evaluating the quality of clustering and therefore spike isolation. Using this method, nearly simultaneously occurring spikes can also be modelled which is a hard task for many of the spike sorting methods. Furthermore, modelling the data with a generative model allows us to generate simulated data.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Brain Computer Interfaces
ID Code:705
Deposited By:Dilan Gorur
Deposited On:29 December 2004