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@ARTICLE{vanAlbada:173339,
author = {van Albada, Sacha and Rennie, Christopher J and Robinson,
Peter A},
title = {{V}ariability of model-free and model-based quantitative
measures of {EEG}},
journal = {Journal of integrative neuroscience},
volume = {6},
number = {2},
issn = {0219-6352},
address = {Singapore},
publisher = {World Scientific Publ.},
reportid = {FZJ-2014-06749},
pages = {279 - 307},
year = {2007},
abstract = {Variable contributions of state and trait to the
electroencephalographic (EEG) signal affect the stability
over time of EEG measures, quite apart from other
experimental uncertainties. The extent of intraindividual
and interindividual variability is an important factor in
determining the statistical, and hence possibly clinical
significance of observed differences in the EEG. This study
investigates the changes in classical quantitative EEG
(qEEG) measures, as well as of parameters obtained by
fitting frequency spectra to an existing continuum model of
brain electrical activity. These parameters may have extra
variability due to model selection and fitting. Besides
estimating the levels of intraindividual and interindividual
variability, we determined approximate time scales for
change in qEEG measures and model parameters. This provides
an estimate of the recording length needed to capture a
given percentage of the total intraindividual variability.
Also, if more precise time scales can be obtained in future,
these may aid the characterization of physiological
processes underlying various EEG measures. Heterogeneity of
the subject group was constrained by testing only healthy
males in a narrow age range (mean = 22.3 years, sd = 2.7).
Eyes-closed EEGs of 32 subjects were recorded at weekly
intervals over an approximately six-week period, of which 13
subjects were followed for a year. QEEG measures, computed
from Cz spectra, were powers in five frequency bands, alpha
peak frequency, and spectral entropy. Of these, theta,
alpha, and beta band powers were most reproducible. Of the
nine model parameters obtained by fitting model predictions
to experiment, the most reproducible ones quantified the
total power and the time delay between cortex and thalamus.
About $95\%$ of the maximum change in spectral parameters
was reached within minutes of recording time, implying that
repeat recordings are not necessary to capture the bulk of
the variability in EEG spectra.},
ddc = {610},
pnm = {331 - Signalling Pathways and Mechanisms in the Nervous
System (POF2-331)},
pid = {G:(DE-HGF)POF2-331},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:17622982},
eprint = {1801.01711},
howpublished = {arXiv:1801.01711},
archivePrefix = {arXiv},
SLACcitation = {$\%\%CITATION$ = $arXiv:1801.01711;\%\%$},
url = {https://juser.fz-juelich.de/record/173339},
}