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The Structure of Chaos: An Empirical Comparison of Fractal Physiology Complexity Indices Using NeuroKit2
Complexity quantification, through entropy, information theory and fractal dimension indices, is gaining a renewed traction in psychophsyiology, as new measures with promising qualities emerge from the computational and mathematical advances. Unfortunately, few studies compare the relationship and o...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9407071/ https://www.ncbi.nlm.nih.gov/pubmed/36010700 http://dx.doi.org/10.3390/e24081036 |
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author | Makowski, Dominique Te, An Shu Pham, Tam Lau, Zen Juen Chen, S. H. Annabel |
author_facet | Makowski, Dominique Te, An Shu Pham, Tam Lau, Zen Juen Chen, S. H. Annabel |
author_sort | Makowski, Dominique |
collection | PubMed |
description | Complexity quantification, through entropy, information theory and fractal dimension indices, is gaining a renewed traction in psychophsyiology, as new measures with promising qualities emerge from the computational and mathematical advances. Unfortunately, few studies compare the relationship and objective performance of the plethora of existing metrics, in turn hindering reproducibility, replicability, consistency, and clarity in the field. Using the NeuroKit2 Python software, we computed a list of 112 (predominantly used) complexity indices on signals varying in their characteristics (noise, length and frequency spectrum). We then systematically compared the indices by their computational weight, their representativeness of a multidimensional space of latent dimensions, and empirical proximity with other indices. Based on these considerations, we propose that a selection of 12 indices, together representing 85.97% of the total variance of all indices, might offer a parsimonious and complimentary choice in regards to the quantification of the complexity of time series. Our selection includes CWPEn, Line Length (LL), BubbEn, MSWPEn, MFDFA (Max), Hjorth Complexity, SVDEn, MFDFA (Width), MFDFA (Mean), MFDFA (Peak), MFDFA (Fluctuation), AttEn. Elements of consideration for alternative subsets are discussed, and data, analysis scripts and code for the figures are open-source. |
format | Online Article Text |
id | pubmed-9407071 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-94070712022-08-26 The Structure of Chaos: An Empirical Comparison of Fractal Physiology Complexity Indices Using NeuroKit2 Makowski, Dominique Te, An Shu Pham, Tam Lau, Zen Juen Chen, S. H. Annabel Entropy (Basel) Article Complexity quantification, through entropy, information theory and fractal dimension indices, is gaining a renewed traction in psychophsyiology, as new measures with promising qualities emerge from the computational and mathematical advances. Unfortunately, few studies compare the relationship and objective performance of the plethora of existing metrics, in turn hindering reproducibility, replicability, consistency, and clarity in the field. Using the NeuroKit2 Python software, we computed a list of 112 (predominantly used) complexity indices on signals varying in their characteristics (noise, length and frequency spectrum). We then systematically compared the indices by their computational weight, their representativeness of a multidimensional space of latent dimensions, and empirical proximity with other indices. Based on these considerations, we propose that a selection of 12 indices, together representing 85.97% of the total variance of all indices, might offer a parsimonious and complimentary choice in regards to the quantification of the complexity of time series. Our selection includes CWPEn, Line Length (LL), BubbEn, MSWPEn, MFDFA (Max), Hjorth Complexity, SVDEn, MFDFA (Width), MFDFA (Mean), MFDFA (Peak), MFDFA (Fluctuation), AttEn. Elements of consideration for alternative subsets are discussed, and data, analysis scripts and code for the figures are open-source. MDPI 2022-07-27 /pmc/articles/PMC9407071/ /pubmed/36010700 http://dx.doi.org/10.3390/e24081036 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Makowski, Dominique Te, An Shu Pham, Tam Lau, Zen Juen Chen, S. H. Annabel The Structure of Chaos: An Empirical Comparison of Fractal Physiology Complexity Indices Using NeuroKit2 |
title | The Structure of Chaos: An Empirical Comparison of Fractal Physiology Complexity Indices Using NeuroKit2 |
title_full | The Structure of Chaos: An Empirical Comparison of Fractal Physiology Complexity Indices Using NeuroKit2 |
title_fullStr | The Structure of Chaos: An Empirical Comparison of Fractal Physiology Complexity Indices Using NeuroKit2 |
title_full_unstemmed | The Structure of Chaos: An Empirical Comparison of Fractal Physiology Complexity Indices Using NeuroKit2 |
title_short | The Structure of Chaos: An Empirical Comparison of Fractal Physiology Complexity Indices Using NeuroKit2 |
title_sort | structure of chaos: an empirical comparison of fractal physiology complexity indices using neurokit2 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9407071/ https://www.ncbi.nlm.nih.gov/pubmed/36010700 http://dx.doi.org/10.3390/e24081036 |
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