Permutation entropy for the characterisation of brain activity recorded with magnetoencephalograms in healthy ageing

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

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

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 magnetoencephalogram (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 five 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.

Original languageBritish English
Article number141
JournalEntropy
Volume19
Issue number4
DOIs
StatePublished - 2017

Keywords

  • Ageing
  • Magnetoencephalogram
  • Modified permutation entropy
  • Permutation entropy

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