Linked Life Data

21315157

Source:http://linkedlifedata.com/resource/pubmed/id/21315157

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2011-3-29
pubmed:abstractText
MEG and EEG data contain additive correlated noise generated by environmental and physiological sources. To suppress this type of spatially coloured noise, source estimation is often performed with spatial whitening based on a measured or estimated noise covariance matrix. However, artifacts that span relatively small noise subspaces, such as cardiac, ocular, and muscle artifacts, are often explicitly removed by a variety of denoising methods (e.g., signal space projection) before source imaging. Here, we introduce a new approach, the spectral signal space projection (S(3)P) algorithm, in which time-frequency (TF)-specific spatial projectors are designed and applied to the noisy TF-transformed data, and whitened source estimation is performed in the TF domain. The approach can be used to derive spectral variants of all linear time domain whitened source estimation algorithms. The denoised sensor and source time series are obtained by the corresponding inverse TF-transform. The method is evaluated and compared with existing subspace projection and signal separation techniques using experimental data. Altogether, S(3)P provides an expanded framework for MEG/EEG data denoising and whitened source imaging in both the time and frequency/scale domains.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
1095-9572
pubmed:author
pubmed:copyrightInfo
Copyright © 2011 Elsevier Inc. All rights reserved.
pubmed:issnType
Electronic
pubmed:day
1
pubmed:volume
56
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
78-92
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Spectral signal space projection algorithm for frequency domain MEG and EEG denoising, whitening, and source imaging.
pubmed:affiliation
Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA. rrramirez@mcw.edu
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't