Neural spike classification utilizing both amplitude and temporal information

J. P. Stitt, R. P. Gaumond, J. L. Frazier, F. E. Hanson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A neural spike classification technique, which augments an amplitude classifier by including temporal information, is presented. A discrete Gaussian approximation of the Bayes classifier for amplitude classification is used. To reduce the number of misclassifications, the joint amplitude-interval classifier is implemented by fitting a gamma probability density function to each of the interspike interval histograms of each of the reference neurons.

Original languageEnglish (US)
Title of host publicationAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
PublisherIEEE
Pages411
Number of pages1
ISBN (Print)0780356756
StatePublished - 1999
EventProceedings of the 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Fall Meeting of the Biomedical Engineering Society (1st Joint BMES / EMBS) - Atlanta, GA, USA
Duration: Oct 13 1999Oct 16 1999

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume1
ISSN (Print)0589-1019

Other

OtherProceedings of the 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Fall Meeting of the Biomedical Engineering Society (1st Joint BMES / EMBS)
CityAtlanta, GA, USA
Period10/13/9910/16/99

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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