Neural spike sorting with spatio-temporal features


Archer, Claude and Hochstenbach, Michiel and Hoede, Kees and Meinsma, Gjerrit and Meijer, Hil and Ali Salah, Albert and Stolk, Chris and Swist, Tomasz and Zyprych, Joanna (2008) Neural spike sorting with spatio-temporal features. In: 63rd European Study Group Mathematics with Industry, 28 Jan - 1 Feb 2008, Enschede, The Netherlands (pp. pp. 21-45).

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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.
Item Type:Conference or Workshop Item
Electrical Engineering, Mathematics and Computer Science (EEMCS)
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