Evidence map›Paper›PMID 36010700›Full record

ArticleEntropy (Basel, Switzerland)2022

The Structure of Chaos: An Empirical Comparison of Fractal Physiology Complexity Indices Using NeuroKit2.

Dominique Makowski, An Shu Te, Tam Pham, Zen Juen Lau, S H Annabel Chen

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Evaluating and Comparing Measures of Aperiodic Neural Activity.bioRxiv : the preprint server for biology · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Dominique MakowskiSchool of Social Sciences, Nanyang Technological University, Singapore 639818, Singapore.ORCID 0000-0001-5375-9967
An Shu TeSchool of Social Sciences, Nanyang Technological University, Singapore 639818, Singapore.ORCID 0000-0001-8008-2824
Tam PhamSchool of Social Sciences, Nanyang Technological University, Singapore 639818, Singapore.ORCID 0000-0002-6392-6703
Zen Juen LauSchool of Social Sciences, Nanyang Technological University, Singapore 639818, Singapore.ORCID 0000-0003-4429-4082
S H Annabel ChenSchool of Social Sciences, Nanyang Technological University, Singapore 639818, Singapore.ORCID 0000-0002-1540-5516

Funding

Ministry of Education MOE2019-T2-1-019Nanyang Technological University 03INS001035C430
6 · The paper itself

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

Indexed as

chaoscomplexityfractalnoisephysiology

Identifiers

PMID36010700
PMCPMC9407071

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.