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Comparative Analysis of the Permutation and Multiscale Entropies for Quantification of the Brain Signal Variability in Naturalistic Scenarios

The Thomas N. Sato BioMEC-X Laboratories, Advanced Telecommunications Research Institute International (ATR), 2-2 Hikaridai Seika-cho, Kyoto 619-02, Japan
Brain Sci. 2020, 10(8), 527; https://doi.org/10.3390/brainsci10080527
Received: 7 July 2020 / Revised: 4 August 2020 / Accepted: 5 August 2020 / Published: 6 August 2020
As alternative entropy estimators, multiscale entropy (MSE) and permutation entropy (PE) are utilized for quantification of the brain function and its signal variability. In this context, their applications are primarily focused on two specific domains: (1) the effect of brain pathology on its function (2) the study of altered states of consciousness. As a result, there is a paucity of research on applicability of these measures in more naturalistic scenarios. In addition, the utility of these measures for quantification of the brain function and with respect to its signal entropy is not well studied. These shortcomings limit the interpretability of the measures when used for quantification of the brain signal entropy. The present study addresses these limitations by comparing MSE and PE with entropy of human subjects’ EEG recordings, who watched short movie clips with negative, neutral, and positive content. The contribution of the present study is threefold. First, it identifies a significant anti-correlation between MSE and entropy. In this regard, it also verifies that such an anti-correlation is stronger in the case of negative rather than positive or neutral affects. Second, it finds that MSE significantly differentiates between these three affective states. Third, it observes that the use of PE does not warrant such significant differences. These results highlight the level of association between brain’s entropy in response to affective stimuli on the one hand and its quantification in terms of MSE and PE on the other hand. This, in turn, allows for more informed conclusions on the utility of MSE and PE for the study and analysis of the brain signal variability in naturalistic scenarios. View Full-Text
Keywords: differential entropy; multi-scale entropy; permutation entropy; whole-brain variability; brain information processing differential entropy; multi-scale entropy; permutation entropy; whole-brain variability; brain information processing
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MDPI and ACS Style

Keshmiri, S. Comparative Analysis of the Permutation and Multiscale Entropies for Quantification of the Brain Signal Variability in Naturalistic Scenarios. Brain Sci. 2020, 10, 527. https://doi.org/10.3390/brainsci10080527

AMA Style

Keshmiri S. Comparative Analysis of the Permutation and Multiscale Entropies for Quantification of the Brain Signal Variability in Naturalistic Scenarios. Brain Sciences. 2020; 10(8):527. https://doi.org/10.3390/brainsci10080527

Chicago/Turabian Style

Keshmiri, Soheil. 2020. "Comparative Analysis of the Permutation and Multiscale Entropies for Quantification of the Brain Signal Variability in Naturalistic Scenarios" Brain Sciences 10, no. 8: 527. https://doi.org/10.3390/brainsci10080527

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