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).
Versions
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BibTeX
@misc{gancio2026exploring,
title = {{Exploring the robustness of permutation entropy analysis to differentiate between closed-eyes and open-eyes resting states}},
author = {Juan Gancio and Natalia López López and Antonio J. Pons and Giulio Tirabassi and Cristina Masoller},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.22265},
eprint = {2609.22265},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.22265},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - UNPB
TI - Exploring the robustness of permutation entropy analysis to differentiate between closed-eyes and open-eyes resting states
AU - Juan Gancio
AU - Natalia López López
AU - Antonio J. Pons
AU - Giulio Tirabassi
AU - Cristina Masoller
PY - 2026
DA - 2026/09/07
PB - arXiv
DO - 10.48550/arxiv.2609.22265
UR - https://arxiv.org/abs/2609.22265
AB - 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).
ER -