Approximate entropy of brain network in the study of hemispheric differences

Francesca Alù, Francesca Miraglia, Alessandro Orticoni, Elda Judica, Maria Cotelli, Paolo Maria Rossini, Fabrizio Vecchio

Research output: Contribution to journalArticlepeer-review

Abstract

Human brain, a dynamic complex system, can be studied with different approaches, including linear and nonlinear ones. One of the nonlinear approaches widely used in electroencephalographic (EEG) analyses is the entropy, the measurement of disorder in a system. The present study investigates brain networks applying approximate entropy (ApEn) measure for assessing the hemispheric EEG differences; reproducibility and stability of ApEn data across separate recording sessions were evaluated. Twenty healthy adult volunteers were submitted to eyes-closed resting EEG recordings, for 80 recordings. Significant differences in the occipital region, with higher values of entropy in the left hemisphere than in the right one, show that the hemispheres become active with different intensities according to the performed function. Besides, the present methodology proved to be reproducible and stable, when carried out on relatively brief EEG epochs but also at a 1-week distance in a group of 36 subjects. Nonlinear approaches represent an interesting probe to study the dynamics of brain networks. ApEn technique might provide more insight into the pathophysiological processes underlying age-related brain disconnection as well as for monitoring the impact of pharmacological and rehabilitation treatments.

Original languageEnglish
Article numberE1220
Number of pages12
JournalEntropy
Volume22
Issue number11
DOIs
Publication statusPublished - Nov 2020

Keywords

  • Brain networks
  • EEG
  • Entropy
  • Left and right

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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