Exploring the robustness of permutation entropy analysis to differentiate between closed-eyes and open-eyes resting states

Abstract

Electroencephalography (EEG) is a noninvasive technology that is widely used to monitor brain states, and many efforts are focused on developing reliable and efficient data analysis methods for EEG recordings. Here, we apply ordinal analysis to the EEG recording of the resting state of 109 healthy subjects measured in two different conditions: with eyes closed (EC state) or eyes open (EO state). We study the robustness of the temporal permutation entropy ($PE$) and the spatial permutation entropy ($SPE$) with respect to the presence of blinking artifacts in the EO recordings, the duration of the recordings, and the number of EEG channels analyzed. We perform a paired statistical test to assess whether these quantities differ significantly in the EO and EC recordings of the same subject. We find that $PE$ and $SPE$ perform surprisingly well, as they detect significant differences when calculated from the raw signals, even within a short time interval ($PE$) or from a reduced number of electrodes ($SPE$).

This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in Gancio, Juan, et al. "Exploring the robustness of permutation entropy analysis to differentiate between closed-eyes and open-eyes resting states." Chaos (2026), and may be found at https://doi.org/10.1063/5.0326211

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