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Spike detection using the continuous wavelet transform

Nenadic, Zoran and Burdick, Joel W. (2005) Spike detection using the continuous wavelet transform. IEEE Transactions on Biomedical Engineering, 52 (1). pp. 74-87. ISSN 0018-9294. doi:10.1109/TBME.2004.839800.

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This paper combines wavelet transforms with basic detection theory to develop a new unsupervised method for robustly detecting and localizing spikes in noisy neural recordings. The method does not require the construction of templates, or the supervised setting of thresholds. We present extensive Monte Carlo simulations, based on actual extracellular recordings, to show that this technique surpasses other commonly used methods in a wide variety of recording conditions. We further demonstrate that falsely detected spikes corresponding to our method resemble actual spikes more than the false positives of other techniques such as amplitude thresholding. Moreover, the simplicity of the method allows for nearly real-time execution.

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Additional Information:© 2005 IEEE. Reprinted with permission. Manuscript received September 26, 2003; revised May 25, 2004. [Posted online: 2004-12-20] This work was supported in part by the National Science Foundation (NSF) under Grant 9402726 and in part by the Defense Advanced Research Projects Agency (DARPA) under Grant MDA972-00-1-0029. The authors would like to acknowledge the anonymous reviewers and the editorial staff of this transactions.
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Defense Advanced Research Projects Agency (DARPA)MDA972-00-1-0029
Subject Keywords:Arrival time estimation, continuous wavelet transform, unsupervised spike detection
Issue or Number:1
Record Number:CaltechAUTHORS:NENieeetbe05
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:4127
Deposited By: Archive Administrator
Deposited On:28 Jul 2006
Last Modified:08 Nov 2021 20:15

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