eprintid: 266
rev_number: 15
eprint_status: archive
userid: 7
dir: disk0/00/00/02/66
datestamp: 2009-11-09 19:12:36
lastmod: 2015-05-29 19:52:57
status_changed: 2009-11-09 19:12:35
type: report
metadata_visibility: show
item_issues_count: 0
creators_name: Archer, Claude
creators_name: Hochstenbach, Michiel
creators_name: Hoede, Kees
creators_name: Meinsma, Gjerrit
creators_name: Meijer, Hil
creators_name: Ali Salah, Albert
creators_name: Stolk, Chris
creators_name: Swist, Tomasz
creators_name: Zyprych, Joanna
title: Neural spike sorting with spatio-temporal features
ispublished: pub
subjects: medicine
studygroups: esgi63
companyname: Philips amc
full_text_status: public
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.
date: 2008
citation:   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.  [Study Group Report]     
document_url: http://miis.maths.ox.ac.uk/miis/266/1/philips_amc.pdf
document_url: http://miis.maths.ox.ac.uk/miis/266/2/philips_ams-report.pdf