Comparison of neural spike classification techniques

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

Comparison of neural spike classification techniques

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

Materials Characterization Lab

Research output: Contribution to journal › Conference article › peer-review

6 Scopus citations

Abstract

This paper presents an Artificial Neural Network (ANN) capable of sorting neural spikes contained in a single-channel multiunit recording. The ANN performs very well when compared with Template Matching and Principal Components, two of the conventional optimal spike classification methods that have been widely used for sorting action potentials.

Original language	English (US)
Pages (from-to)	1092-1094
Number of pages	3
Journal	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume	3
State	Published - 1997
Event	Proceedings of the 1997 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Chicago, IL, USA Duration: Oct 30 1997 → Nov 2 1997

All Science Journal Classification (ASJC) codes

Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Health Informatics

Cite this

@article{53f82e056d37425980b2f194cf86c122,

title = "Comparison of neural spike classification techniques",

abstract = "This paper presents an Artificial Neural Network (ANN) capable of sorting neural spikes contained in a single-channel multiunit recording. The ANN performs very well when compared with Template Matching and Principal Components, two of the conventional optimal spike classification methods that have been widely used for sorting action potentials.",

author = "Stitt, {J. P.} and Gaumond, {R. P.} and Frazier, {J. L.} and Hanson, {F. E.}",

year = "1997",

language = "English (US)",

volume = "3",

pages = "1092--1094",

journal = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",

issn = "0589-1019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "Proceedings of the 1997 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society ; Conference date: 30-10-1997 Through 02-11-1997",

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T1 - Comparison of neural spike classification techniques

AU - Stitt, J. P.

AU - Gaumond, R. P.

AU - Frazier, J. L.

AU - Hanson, F. E.

PY - 1997

Y1 - 1997

N2 - This paper presents an Artificial Neural Network (ANN) capable of sorting neural spikes contained in a single-channel multiunit recording. The ANN performs very well when compared with Template Matching and Principal Components, two of the conventional optimal spike classification methods that have been widely used for sorting action potentials.

AB - This paper presents an Artificial Neural Network (ANN) capable of sorting neural spikes contained in a single-channel multiunit recording. The ANN performs very well when compared with Template Matching and Principal Components, two of the conventional optimal spike classification methods that have been widely used for sorting action potentials.

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UR - http://www.scopus.com/inward/citedby.url?scp=0031294912&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:0031294912

SN - 0589-1019

VL - 3

SP - 1092

EP - 1094

JO - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

JF - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

T2 - Proceedings of the 1997 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Y2 - 30 October 1997 through 2 November 1997

ER -

Comparison of neural spike classification techniques

Abstract

All Science Journal Classification (ASJC) codes

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