| A wavelet packet model of evoked potentials. | |
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MedLine Citation:
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PMID: 10080865 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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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. |
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Authors:
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J Raz; L Dickerson; B Turetsky |
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Publication Detail:
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Type: Journal Article; Research Support, U.S. Gov't, P.H.S. |
Journal Detail:
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Title: Brain and language Volume: 66 ISSN: 0093-934X ISO Abbreviation: Brain Lang Publication Date: 1999 Jan |
Date Detail:
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Created Date: 1999-06-01 Completed Date: 1999-06-01 Revised Date: 2007-11-14 |
Medline Journal Info:
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Nlm Unique ID: 7506220 Medline TA: Brain Lang Country: UNITED STATES |
Other Details:
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Languages: eng Pagination: 61-88 Citation Subset: IM |
Copyright Information:
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Copyright 1999 Academic Press. |
Affiliation:
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Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109-2029, USA. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Animals Brain / physiology* Cats Electroencephalography Evoked Potentials* Models, Biological* |
| Grant Support | |
ID/Acronym/Agency:
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R29 MH51310/MH/NIMH NIH HHS |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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