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Title: | Regularity and randomness in ageing : differences in resting-state EEG complexity measured by largest Lyapunov exponent | Authors: | Ma, MKH Fong, MCM Xie, C Lee, T Chen, G Wang, W S |
Issue Date: | Dec-2021 | Source: | NeuroImage, Dec. 2021, v. 1, no. 4, 100054 | Abstract: | The loss of complexity in ageing hypothesis (LOCH) has found support from EEG studies, most of which adopted signal-domain complexity measures. The present study adopted the largest Lyapunov exponent (LLE) to measure complexity from a nonlinear dynamical systems perspective. A total of 144 participants were included and divided into young, young-old and old-old groups. Both sensor-space and source-space results showed significantly lower LLE for older than younger adults. The age-related differences were region-dependent, being most prominent in the frontal region, followed by bilateral temporal regions. The occipital region showed non-significant differences. Significant reduction of LLE in the posterior cingulate was also observed by virtue of the source-space analysis. We also evaluated the relationships between LLE and other complexity measures. The most intriguing result was the negative correlation between LLE and Lempel-Ziv complexity (LZC). The age-related decrease in LLE indicated a higher regularity in dynamics, while the higher LZC indicated a higher randomness in the signal domain. The new findings support the LOCH by demonstrating the simultaneous increase in regularity and randomness. | Keywords: | Complexity Ageing EEG Largest lyapunov exponent Resting state |
Publisher: | Academic Press | Journal: | NeuroImage | ISSN: | 1053-8119 | EISSN: | 1095-9572 | DOI: | 10.1016/j.ynirp.2021.100054 | Rights: | © 2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). The following publication Ma, M. K.-H., Fong, M. C.-M., Xie, C., Lee, T., Chen, G., & Wang, W. S. (2021). Regularity and randomness in ageing: Differences in resting-state EEG complexity measured by largest Lyapunov exponent. Neuroimage: Reports, 1(4), 100054 is available at https://dx.doi.org/10.1016/j.ynirp.2021.100054. |
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