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  Optimal filtering for spike sorting of multi-site electrode recordings

Vollgraf, R., Munk, M., & Obermayer, K. (2005). Optimal filtering for spike sorting of multi-site electrode recordings. Network: Computation in Neural Systems, 16(1), 85-113. doi:10.1080/09548980500275378.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-D5EB-E Version Permalink: http://hdl.handle.net/21.11116/0000-0004-DCA8-7
Genre: Journal Article

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Vollgraf, R, Author
Munk, M1, Author              
Obermayer, K, Author
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1External Organizations, ou_persistent22              

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 Abstract: We derive an optimal linear filter, to reduce the distortions of the peak amplitudes of action potentials in extracellular multitrode recordings, which are due to background activity and overlapping spikes. This filter is being learned very efficiently from the raw recordings in an unsupervised manner and responds to the average waveform with an impulse of minimal width. The average waveform does not have to be known in advance, but is learned together with the optimal filter. The peak amplitude of a filtered waveform is a more reliable estimate for the amplitude of an action potential than the peak of the biphasic waveform and can improve the accuracy of the event detection and clustering procedures. We demonstrate a spike-sorting application, in which events are detected using the Mahalanobis distance in the N-dimensional space of filtered recordings as a distance measure, and the event amplitudes of the filtered recordings are clustered to assign events to individual units. This method is fast and robust, and we show its performance by applying it to real tetrode recordings of spontaneous activity in the visual cortex of an anaesthetized cat and to realistic artificial data derived therefrom.

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 Dates: 2005-03
 Publication Status: Published in print
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 Rev. Method: -
 Identifiers: DOI: 10.1080/09548980500275378
BibTex Citekey: VollgrafMO2005
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Title: Network: Computation in Neural Systems
  Other : Netw.-Comput. Neural Syst.
Source Genre: Journal
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Publ. Info: Bristol : IOP Pub.
Pages: - Volume / Issue: 16 (1) Sequence Number: - Start / End Page: 85 - 113 Identifier: ISSN: 0954-898X
CoNE: https://pure.mpg.de/cone/journals/resource/954925576018