Paper Info
Title
The Structure of Chaos: An Empirical Comparison of Fractal Physiology Complexity Indices Using NeuroKit2
Abstract
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.
Year
DOI
Venue
2022
10.3390/e24081036
ENTROPY
Keywords
DocType
Volume
chaos, complexity, fractal, physiology, noise
Journal
24
Issue
ISSN
Citations 
8
1099-4300
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Dominique Makowski100.68
An Shu Te200.34
Tam Pham300.68
Zen Juen Lau400.68
S. H. Annabel Chen500.34