Document Detail


A wavelet packet model of evoked potentials.
MedLine Citation:
PMID:  10080865     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The standard methods for decomposition and analysis of evoked potentials are bandpass filtering, identification of peak amplitudes and latencies, and principal component analysis (PCA). We discuss the limitations of these and other approaches and introduce wavelet packet analysis. Then we propose the "single-channel wavelet packet model," a new approach in which a unique decomposition is achieved using prior time-frequency information and differences in the responses of the components to changes in experimental conditions. Orthogonal sets of wavelet packets allow a parsimonious time-frequency representation of the components. The method allows energy in some wavelet packets to be shared among two or more components, so the components are not necessarily orthogonal. The single-channel wavelet packet model and PCA both require constraints to achieve a unique decomposition. In PCA, however, the constraints are defined by mathematical convenience and may be unrealistic. In the single-channel wavelet packet model, the constraints are based on prior scientific knowledge. We give an application of the method to auditory evoked potentials recorded from cats. The good frequency resolution of wavelet packets allows us to separate superimposed components in these data. Our present approach yields estimates of component waveforms and the effects of experiment conditions on the amplitude of the components. We discuss future extensions that will provide confidence intervals and p values, allow for latency changes, and represent multichannel data.
Authors:
J Raz; L Dickerson; B Turetsky
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Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, P.H.S.    
Journal Detail:
Title:  Brain and language     Volume:  66     ISSN:  0093-934X     ISO Abbreviation:  Brain Lang     Publication Date:  1999 Jan 
Date Detail:
Created Date:  1999-06-01     Completed Date:  1999-06-01     Revised Date:  2007-11-14    
Medline Journal Info:
Nlm Unique ID:  7506220     Medline TA:  Brain Lang     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  61-88     Citation Subset:  IM    
Copyright Information:
Copyright 1999 Academic Press.
Affiliation:
Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109-2029, USA.
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MeSH Terms
Descriptor/Qualifier:
Animals
Brain / physiology*
Cats
Electroencephalography
Evoked Potentials*
Models, Biological*
Grant Support
ID/Acronym/Agency:
R29 MH51310/MH/NIMH NIH HHS

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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