Neural spike sorting with spatio-temporal features

Claude Archer, Michiel Hochstenbach, Kees Hoede, Gjerrit Meinsma, Hil Meijer, Albert Ali Salah, Chris Stolk, Tomasz Swist, Joanna Zyprych

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

52 Downloads (Pure)

Abstract

The paper analyses signals that have been measured by brain probes during surgery. First background noise is removed from the signals. The remaining signals are a superposition of spike trains which are subsequently assigned to different families. For this two techniques are used: classic PCA and code vectors. Both techniques confirm that amplitude is the distinguishing feature of spikes. Finally the presence of various types of periodicity in spike trains are examined using correlation and the interval shift histogram. The results allow the development of a visual aid for surgeons.
Original languageEnglish
Title of host publicationProceedings of the 63rd European Study Group Mathematics with Industry
Subtitle of host publicationEnschede, The Netherlands, 28 January – 1 February, 2008
EditorsOnno Bokhove, Johann Hurink, Gjerrit Meinsma, Chris Stolk, Michel Vellekoop
Place of PublicationAmsterdam
PublisherCentrum voor Wiskunde en Informatica
Pages21-45
Number of pages25
ISBN (Print)978-90-365-2779-8
Publication statusPublished - 2008
Event63rd European Study Group Mathematics with Industry, SWI 2008 - University of Twente, Enschede, Netherlands
Duration: 28 Jan 20081 Feb 2008
Conference number: 63

Publication series

NameCWI syllabus
PublisherCWI (Centrum voor Wiskunde en Informatica)

Conference

Conference63rd European Study Group Mathematics with Industry, SWI 2008
Abbreviated titleSWI
CountryNetherlands
CityEnschede
Period28/01/081/02/08

Keywords

  • Spike sorting
  • PCA
  • interspike interval histogram
  • IR-65335
  • Deep Brain Stimulation
  • METIS-255153
  • EWI-14946

Fingerprint Dive into the research topics of 'Neural spike sorting with spatio-temporal features'. Together they form a unique fingerprint.

Cite this