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A Method for Detection and Classification of Events in Neural Activity

Bokil, Hemant S. and Pesaran, Bijan and Andersen, Richard A. and Mitra, Parta P. (2006) A Method for Detection and Classification of Events in Neural Activity. IEEE Transactions on Biomedical Engineering, 53 (8). pp. 1678-1687. ISSN 0018-9294. https://resolver.caltech.edu/CaltechAUTHORS:BOKieeetbe06

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Abstract

We present a method for the real time prediction of punctuate events in neural activity, based on the time-frequency spectrum of the signal, applicable both to continuous processes like local field potentials (LFPs) as well as to spike trains. We test it on recordings of LFP and spiking activity acquired previously from the lateral intraparietal area (LIP) of macaque monkeys performing a memory-saccade task. In contrast to earlier work, where trials with known start times were classified, our method detects and classifies trials directly from the data. It provides a means to quantitatively compare and contrast the content of LFP signals and spike trains: we find that the detector performance based on the LFP matches the performance based on spike rates. The method should find application in the development of neural prosthetics based on the LFP signal. Our approach uses a new feature vector, which we call the 2d cepstrum.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/TBME.2006.877802DOIUNSPECIFIED
ORCID:
AuthorORCID
Andersen, Richard A.0000-0002-7947-0472
Additional Information:© 2006 IEEE. Reprinted with permission. Manuscript received July 29, 2005; revised February 19, 2006. [Posted online: 2006-07-17] This work was supported in part by Defense Advanced Research Projects Agency (DARPA), in part by the McKnight Foundation, in part by the Swartz Foundation, in part by the National Institutes of Health (NIH) under Grant R01 MH62528-02 and Grant EY 13337-03. The work of R. A. Anderson was supported in part by a Boswell Professorship. The authors acknowledge and thank Dr. J. Pezaris and Dr. M. Sahani for recording the LIP data which we used to test the algorithm. The authors declare that they have no competing financial interest.
Funders:
Funding AgencyGrant Number
Defense Advanced Research Projects Agency (DARPA)UNSPECIFIED
McKnight FoundationUNSPECIFIED
Swartz FoundationUNSPECIFIED
NIHR01 MH62528-02
NIHEY 13337-03
James G. Boswell FoundationUNSPECIFIED
Subject Keywords:Cepstral analysis, decoding, multitaper spectral analysis, nervous system, prediction methods
Issue or Number:8
Record Number:CaltechAUTHORS:BOKieeetbe06
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:BOKieeetbe06
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:2660
Collection:CaltechAUTHORS
Deposited By: Archive Administrator
Deposited On:01 Nov 2006
Last Modified:02 Oct 2019 22:55

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