Permutation Entropy for the Characterisation of Brain Activity Recorded with Magnetoencephalograms in Healthy Ageing

Shumbayawonda, Elizabeth; Fernández, Alberto; Hughes, Michael; Abásolo, Daniel

doi:10.3390/e19040141

Cited by 19 publications

(18 citation statements)

References 58 publications

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“…Nevertheless, similar to EEG, MEG analysis at the sensor level is affected by volume conduction, although to a much smaller degree [ 12 ]. MEG data have been used to: identify epileptic zones [ 13 ], investigate brain function, evaluate neurofeedback [ 14 ], determine the effects of pathology, investigate effect of cognitive decline [ 15 ], and, to determine the effects of ageing on the brain [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

“…Once the brain recordings are obtained, a wide range of linear and non-linear and processing techniques, such as causality [ 17 ], entropy [ 16 ], synchronisation [ 18 ], correlation [ 19 ], and complexity [ 4 ], can be applied to them. Complexity is a concept stemming from non-linear analysis methods that could be applied to evaluate changes in brain activity recorded in MEG signals (see [ 20 ] for a detailed description of complexity).…”

Section: Introductionmentioning

confidence: 99%

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Complexity Changes in Brain Activity in Healthy Ageing: A Permutation Lempel-Ziv Complexity Study of Magnetoencephalograms

Shumbayawonda

Tosun

Fernández

et al. 2018

Entropy

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Maturation and ageing, which can be characterised by the dynamic changes in brain morphology, can have an impact on the physiology of the brain. As such, it is possible that these changes can have an impact on the magnetic activity of the brain recorded using magnetoencephalography. In this study changes in the resting state brain (magnetic) activity due to healthy ageing were investigated by estimating the complexity of magnetoencephalogram (MEG) signals. The main aim of this study was to identify if the complexity of background MEG signals changed significantly across the human lifespan for both males and females. A sample of 177 healthy participants (79 males and 98 females aged between 21 and 80 and grouped into 3 categories i.e., early-, mid-and late-adulthood) was used in this investigation. This investigation also extended to evaluating if complexity values remained relatively stable during the 5 min recording. Complexity was estimated using permutation Lempel-Ziv complexity, a recently introduced complexity metric, with a motif length of 5 and a lag of 1. Effects of age and gender were investigated in the MEG channels over 5 brain regions, i.e., anterior, central, left lateral, posterior, and, right lateral, with highest complexity values observed in the signals recorded by the channels over the anterior and central regions of the brain. Results showed that while changes due to age had a significant effect on the complexity of the MEG signals recorded over 5 brain regions, gender did not have a significant effect on complexity values in all age groups investigated. Moreover, although some changes in complexity were observed between the different minutes of recording, due to the small magnitude of the changes it was concluded that practical significance might outweigh statistical significance in this instance. The results from this study can contribute to form a fingerprint of the characteristics of healthy ageing in MEGs that could be useful when investigating changes to the resting state activity due to pathology.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Complexity Changes in Brain Activity in Healthy Ageing: A Permutation Lempel-Ziv Complexity Study of Magnetoencephalograms

Shumbayawonda

Tosun

Fernández

et al. 2018

Entropy

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“…However, our results do not depend on the temporal scales, but they reflect the changes in all the frequency bandwidth and are consistent across spatial scales. Increased complexity of MEG signals with age were also reported in [8] and [9]. Evidences of aging-related changes in the Fourier spectrum of EEG with a decrease in power for low frequencies and an increase for high frequencies were also reported in [38], [39], [40].…”

Section: Discussionmentioning

confidence: 78%

“…Fernández et al found significant increases in Lempel-Ziv complexity measures with age [8]. Shumbayawonda et al confirmed increases in permutation entropy with age [9], and in permutation Lempel-Ziv complexity with age [10]. By contrast, Coquelet et al did not find any significant agerelated changes in both static and dynamic power envelopebased connectivity from resting-state MEG data, suggesting that the electrophysiological connectome is maintained in healthy aging [4].…”

Section: Introductionmentioning

confidence: 98%

Multichannel Time–Frequency Complexity Measures for the Analysis of Age-Related Changes in Neuromagnetic Resting-State Activity

Colominas

Wens

Mary

et al. 2019

IEEE J. Biomed. Health Inform.

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We propose new multichannel time-frequency complexity measures to evaluate differences on magnetoencephalograpy (MEG) recordings between healthy young and old subjects at rest at different spatial scales. After reviewing the Rényi and singular value decomposition entropies based on time-frequency representations, we introduce multichannel generalizations, using multilinear singular value decomposition for one of them. We test these quantities on synthetic data, illustrating how the introduced complexity measures focus on number of components, nonstationarity and similarity across channels. Friedman tests are used to confirm the differences between young and old groups, and heterogeneity within groups. Experimental results show a consistent increase in complexity measures for the old group. When analyzing the topographical distribution of complexity values, we found clusters in the frontal sensors. The complexity measures here introduced seem to be a better indicator of the neurophysiologic changes of aging than power envelope connectivity. Here we applied new multichannel time-frequency complexity measures to resting-state MEG recordings from healthy young and old subjects. We showed that these features are able to reveal regional clusters. The multichannel time-frequency complexities can be used to monitor the aging of subjects. They also allow a mutual information approach, and could be applied to a wider range of problems.

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“…Moreover, our correlation analysis showed that higher complexity values over highly overlapping regions to the ones mentioned above were associated with larger hippocampal volumes only in females. Different techniques were applied over the years to acquire more information related to the differences between males and females on the activity of the brain [39,[41][42][43][44]. Detection of these sex differences is not a trivial task as male and female activity in MEG signals is very similar, especially for healthy subjects.…”

Section: Discussionmentioning

confidence: 99%

Sex Differences in the Complexity of Healthy Older Adults’ Magnetoencephalograms

Shumbayawonda

Abásolo

López‐Sanz

et al. 2019

Entropy

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The analysis of resting-state brain activity recording in magnetoencephalograms (MEGs) with new algorithms of symbolic dynamics analysis could help obtain a deeper insight into the functioning of the brain and identify potential differences between males and females. Permutation Lempel-Ziv complexity (PLZC), a recently introduced non-linear signal processing algorithm based on symbolic dynamics, was used to evaluate the complexity of MEG signals in source space. PLZC was estimated in a broad band of frequencies (2–45 Hz), as well as in narrow bands (i.e., theta (4–8 Hz), alpha (8–12 Hz), low beta (12–20 Hz), high beta (20–30 Hz), and gamma (30–45 Hz)) in a sample of 98 healthy elderly subjects (49 males, 49 female) aged 65–80 (average age of 72.71 ± 4.22 for males and 72.67 ± 4.21 for females). PLZC was significantly higher for females than males in the high beta band at posterior brain regions including the precuneus, and the parietal and occipital cortices. Further statistical analyses showed that higher complexity values over highly overlapping regions than the ones mentioned above were associated with larger hippocampal volumes only in females. These results suggest that sex differences in healthy aging can be identified from the analysis of magnetoencephalograms with novel signal processing methods.

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Permutation Entropy for the Characterisation of Brain Activity Recorded with Magnetoencephalograms in Healthy Ageing

Cited by 19 publications

References 58 publications

Complexity Changes in Brain Activity in Healthy Ageing: A Permutation Lempel-Ziv Complexity Study of Magnetoencephalograms

Complexity Changes in Brain Activity in Healthy Ageing: A Permutation Lempel-Ziv Complexity Study of Magnetoencephalograms

Multichannel Time–Frequency Complexity Measures for the Analysis of Age-Related Changes in Neuromagnetic Resting-State Activity

Sex Differences in the Complexity of Healthy Older Adults’ Magnetoencephalograms

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