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Dimensional complexity and spectral properties of the human sleep EEG

Dimensional complexity and spectral properties of the human sleep EEG
Dimensional complexity and spectral properties of the human sleep EEG
Objective: The relevance of the dimensional complexity (DC) for the analysis of sleep EEG data is investigated and compared to linear measures.
Methods: We calculated DC of artifact-free 1 min segments of all-night sleep EEG recordings of 4 healthy young subjects. Non-linearity was tested by comparing with DC values of surrogate data. Linear properties of the segments were characterized by estimating the self-similarity exponent ? based on the detrended fluctuation analysis which quantifies the persistence of the signal and by calculating spectral power in the delta, theta, alpha and sigma bands, respectively.
Results: We found weak nonlinear signatures in all sleep stages, but most pronounced in sleep stage 2. Strong correlations between DC and linear measures were established for the self-similarity exponent ? and delta power, respectively.
Conclusions: The dimensional complexity of the sleep EEG is influenced by both linear and nonlinear features. It cannot be directly interpreted as a nonlinear synchronization measure of brain activity, but yields valuable information when combined with the analysis of linear measures.
self-similarity exponent, spectral power, nonlinear analysis, surrogate analysis
199-209
Shen, Y.
b7aa33ab-b778-4454-a00c-f40c4ca46539
Olbrich, E.
09ca5fb1-9d9a-46a4-89aa-fc2726d7c258
Achermann, P.
ebb236fd-19da-4e30-ac96-2797784632f0
Meier, P.F.
803df7a3-67f8-46af-bae6-1c8fc2b63535
Shen, Y.
b7aa33ab-b778-4454-a00c-f40c4ca46539
Olbrich, E.
09ca5fb1-9d9a-46a4-89aa-fc2726d7c258
Achermann, P.
ebb236fd-19da-4e30-ac96-2797784632f0
Meier, P.F.
803df7a3-67f8-46af-bae6-1c8fc2b63535

Shen, Y., Olbrich, E., Achermann, P. and Meier, P.F. (2003) Dimensional complexity and spectral properties of the human sleep EEG. Clinical Neurophysiology, 114 (2), 199-209. (doi:10.1016/S1388-2457(02)00338-3).

Record type: Article

Abstract

Objective: The relevance of the dimensional complexity (DC) for the analysis of sleep EEG data is investigated and compared to linear measures.
Methods: We calculated DC of artifact-free 1 min segments of all-night sleep EEG recordings of 4 healthy young subjects. Non-linearity was tested by comparing with DC values of surrogate data. Linear properties of the segments were characterized by estimating the self-similarity exponent ? based on the detrended fluctuation analysis which quantifies the persistence of the signal and by calculating spectral power in the delta, theta, alpha and sigma bands, respectively.
Results: We found weak nonlinear signatures in all sleep stages, but most pronounced in sleep stage 2. Strong correlations between DC and linear measures were established for the self-similarity exponent ? and delta power, respectively.
Conclusions: The dimensional complexity of the sleep EEG is influenced by both linear and nonlinear features. It cannot be directly interpreted as a nonlinear synchronization measure of brain activity, but yields valuable information when combined with the analysis of linear measures.

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Published date: 2003
Keywords: self-similarity exponent, spectral power, nonlinear analysis, surrogate analysis
Organisations: Operational Research

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Local EPrints ID: 29754
URI: http://eprints.soton.ac.uk/id/eprint/29754
PURE UUID: ec1d2922-260b-49e9-82cf-7e92683bdfd0

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Date deposited: 12 May 2006
Last modified: 15 Mar 2024 07:34

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Contributors

Author: Y. Shen
Author: E. Olbrich
Author: P. Achermann
Author: P.F. Meier

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