Entropy as Measure of Brain Networks’ Complexity in Eyes Open and Closed Conditions

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

doi:10.3390/sym13112178

Abstract

Brain complexity can be revealed even through a comparison between two trivial conditions, such as eyes open and eyes closed (EO and EC respectively) during resting. Electroencephalogram (EEG) has been widely used to investigate brain networks, and several non-linear approaches have been applied to investigate EO and EC signals modulation, both symmetric and not. Entropy is one of the approaches used to evaluate the system disorder. This study explores the differences in the EO and EC awake brain dynamics by measuring entropy. In particular, an approximate entropy (ApEn) was measured, focusing on the specific cerebral areas (frontal, central, parietal, occipital, temporal) on EEG data of 37 adult healthy subjects while resting. Each participant was submitted to an EO and an EC resting EEG recording in two separate sessions. The results showed that in the EO condition the cerebral networks of the subjects are characterized by higher values of entropy than in the EC condition. All the cerebral regions are subjected to this chaotic behavior, symmetrically in both hemispheres, proving the complexity of networks dynamics dependence from the subject brain state. Remarkable dynamics regarding cerebral networks during simple resting and awake brain states are shown by entropy. The application of this parameter can be also extended to neurological conditions, to establish and monitor personalized rehabilitation treatments.

Highlights

The first electroencephalographic (EEG) recording was performed in 1924 by the German neurologist Hans Berger, the inventor of this brain electrical activity recording technique
The Duncan post-hoc testing (p < 0.001) revealed higher entropy values in the frontal, central, parietal, occipital and temporal regions of gions of magenta interest (ROIs) during the EO condition compared with the EC one, for all the investigated brain areas
The current results revealed that a higher entropy characterizes human brain networks The current results revealed that a higher entropy characterizes human brain netwhile subjects keep their eyes open

Summary

Introduction

The first electroencephalographic (EEG) recording was performed in 1924 by the German neurologist Hans Berger, the inventor of this brain electrical activity recording technique. Since Berger published the first paper about scalp EEG, this technique has been widely applied to the study of the brain [2], both with the linear and nonlinear approach His findings have been confirmed by several following theories: these demonstrate that alpha desynchronization (due to the visual input in EO condition) reveals the increment of functional innervation of the visual system, which leads to an activation of a larger area of cortex and reflects the interactions of cortical and thalamo-cortical systems that aid the information flow [3,4,5]. The same applies to healthy young adults, in which the small-world value increases from EC to EO states in the alpha band and reduces slightly both in the theta and in the beta (4–7 Hz and 14–30 Hz respectively) band [11]

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