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

Shumbayawonda, Elizabeth, Fernández, A, Hughes, Michael and Abasolo, Daniel Emilio (2017) Permutation Entropy for the Characterisation of Brain Activity Recorded with Magnetoencephalograms in Healthy Ageing Entropy: An International and Interdisciplinary Journal of Entropy and Information Studies, 19 (141).

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Abstract

The characterisation of healthy ageing of the brain could help create a fingerprint of normal ageing that might assist in the early diagnosis of neurodegenerative conditions. This study examined changes in resting state MEG permutation entropy due to age and gender in a sample of 220 healthy participants (98 males and 122 females, ages ranging between 7 and 84). Entropy was quantified using normalised permutation entropy and modified permutation entropy, with an embedding dimension of 5 and a lag of 1 as the input parameters for both algorithms. Effects of age were observed over the 5 regions of the brain i.e. anterior, central, posterior, and left and right lateral, with the anterior and central regions containing the highest permutation entropy. Statistically significant differences due to age were observed in the different brain regions for both genders, with the evolutions described using the fitting of polynomial regressions. Nevertheless, no significant differences between the genders were observed across all ages. These results suggest that the evolution of entropy in the background brain activity, quantified with permutation entropy algorithms, might be considered an alternative illustration of a ‘nominal’ physiological rhythm.

Item Type: Article
Subjects : Mechanical Engineering Science
Divisions : Faculty of Engineering and Physical Sciences > Mechanical Engineering Sciences
Authors :
NameEmailORCID
Shumbayawonda, Elizabethe.shumbayawonda@surrey.ac.ukUNSPECIFIED
Fernández, AUNSPECIFIEDUNSPECIFIED
Hughes, MichaelM.Hughes@surrey.ac.ukUNSPECIFIED
Abasolo, Daniel EmilioD.Abasolo@surrey.ac.ukUNSPECIFIED
Date : 25 March 2017
Identification Number : 10.3390/e19040141
Copyright Disclaimer : © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Uncontrolled Keywords : permutation entropy; modified permutation entropy; magnetoencephalogram; ageing
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 22 Mar 2017 18:36
Last Modified : 19 Jul 2017 13:44
URI: http://epubs.surrey.ac.uk/id/eprint/813838

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