Towards the Understanding of Healthy and Pathological Aging Through MEG

Maestú, Fernando; Solesio-Jofre, Elena; Bajo, Ricardo

doi:10.1007/978-3-319-62657-4_28-1

Cited by 1 publication

(1 citation statement)

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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%

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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