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Optimal Neural Spike Classification

Atiya, Amir F. and Bower, James M. (1988) Optimal Neural Spike Classification. In: Neural Information Processing Systems. American Institute of Physics , New York, NY, pp. 95-102. ISBN 0883185695.

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Being able to record the electrical activities of a number of neurons simultaneously is likely to be important in the study of the functional organization of networks of real neurons. Using one extracellular microelectrode to record from several neurons is one approach to studying the response properties of sets of adjacent and therefore likely related neurons. However, to do this, it is necessary to correctly classify the signals generated by these different neurons. This paper considers this problem of classifying the signals in such an extracellular recording, based upon their shapes, and specifically considers the classification of signals in the case when spikes overlap temporally.

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Additional Information:© American Institute of Physics 1988. Our thanks to Dr. Yaser Abu-Mostafa for his assistance with this work. This project was supported by the Caltech Program of Advanced Technology (sponsored by Aerojet, GM, GTE, and TRW), and the Joseph Drown Foundation.
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Joseph Drown FoundationUNSPECIFIED
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:63460
Deposited By: Kristin Buxton
Deposited On:19 Jan 2016 22:41
Last Modified:03 Oct 2019 09:28

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