Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Standard multiscale entropy reflects neural dynamics at mismatched temporal scales: What’s signal irregularity got to do with it?

View ORCID ProfileJulian Q. Kosciessa, View ORCID ProfileNiels A. Kloosterman, View ORCID ProfileDouglas D. Garrett
doi: https://doi.org/10.1101/752808
Julian Q. Kosciessa
1Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
2Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
3Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Julian Q. Kosciessa
  • For correspondence: kosciessa@mpib-berlin.mpg.de garrett@mpib-berlin.mpg.de
Niels A. Kloosterman
1Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
2Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Niels A. Kloosterman
Douglas D. Garrett
1Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
2Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Douglas D. Garrett
  • For correspondence: kosciessa@mpib-berlin.mpg.de garrett@mpib-berlin.mpg.de
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Data/Code
  • Preview PDF
Loading

Abstract

Multiscale Entropy (MSE) is used to characterize the temporal irregularity of neural time series patterns. Due to its’ presumed sensitivity to non-linear signal characteristics, MSE is typically considered a complementary measure of brain dynamics to signal variance and spectral power. However, the divergence between these measures is often unclear in application. Furthermore, it is commonly assumed (yet sparingly verified) that entropy estimated at specific time scales reflects signal irregularity at those precise time scales of brain function. We argue that such assumptions are not tenable. Using simulated and empirical electroencephalogram (EEG) data from 47 younger and 52 older adults, we indicate strong and previously underappreciated associations between MSE and spectral power, and highlight how these links preclude traditional interpretations of MSE time scales. Specifically, we show that the typical definition of temporal patterns via “similarity bounds” biases coarse MSE scales – that are thought to reflect slow dynamics – by high-frequency dynamics. Moreover, we demonstrate that entropy at fine time scales – presumed to indicate fast dynamics – is highly sensitive to broadband spectral power, a measure dominated by low-frequency contributions. Jointly, these issues produce counterintuitive reflections of frequency-specific content on MSE time scales. We emphasize the resulting inferential problems in a conceptual replication of cross-sectional age differences at rest, in which scale-specific entropy age effects could be explained by spectral power differences at mismatched temporal scales. Furthermore, we demonstrate how such problems may be alleviated, resulting in the indication of scale-specific age differences in rhythmic irregularity. By controlling for narrowband contributions, we indicate that spontaneous alpha rhythms during eyes open rest transiently reduce broadband signal irregularity. Finally, we recommend best practices that may better permit a valid estimation and interpretation of neural signal irregularity at time scales of interest.

Author Summary Brain signals exhibit a wealth of dynamic patterns that that are thought to reflect ongoing neural computations. Multiscale sample entropy (MSE) intends to describe the temporal irregularity of such patterns at multiple time scales of brain function. However, the notion of time scales may often be unintuitive. In particular, traditional implementations of MSE are sensitive to slow fluctuations at fine time scales, and fast dynamics at coarse time scales. This conceptual divergence is often overlooked and may lead to difficulties in establishing the unique contribution of MSE to effects of interest over more established spectral power. Using simulations and empirical data, we highlight these issues and provide evidence for their relevance for valid practical inferences. We further highlight that standard MSE and traditional spectral power are highly collinear in our example. Finally, our analyses indicate that spectral filtering can be used to estimate temporal signal irregularity at matching and intuitive time scales. To guide future studies, we make multiple recommendations based on our observations. We believe that following these suggestions may advance our understanding of the unique contributions of neural signal irregularity to neural and cognitive function across the lifespan.

Footnotes

  • https://osf.io/q3vxm/

  • https://git.mpib-berlin.mpg.de/LNDG/rhythms_entropy

  • https://github.com/LNDG/mMSE

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted March 31, 2020.
Download PDF
Data/Code
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Standard multiscale entropy reflects neural dynamics at mismatched temporal scales: What’s signal irregularity got to do with it?
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Standard multiscale entropy reflects neural dynamics at mismatched temporal scales: What’s signal irregularity got to do with it?
Julian Q. Kosciessa, Niels A. Kloosterman, Douglas D. Garrett
bioRxiv 752808; doi: https://doi.org/10.1101/752808
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Standard multiscale entropy reflects neural dynamics at mismatched temporal scales: What’s signal irregularity got to do with it?
Julian Q. Kosciessa, Niels A. Kloosterman, Douglas D. Garrett
bioRxiv 752808; doi: https://doi.org/10.1101/752808

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Neuroscience
Subject Areas
All Articles
  • Animal Behavior and Cognition (4682)
  • Biochemistry (10357)
  • Bioengineering (7670)
  • Bioinformatics (26330)
  • Biophysics (13523)
  • Cancer Biology (10683)
  • Cell Biology (15438)
  • Clinical Trials (138)
  • Developmental Biology (8497)
  • Ecology (12820)
  • Epidemiology (2067)
  • Evolutionary Biology (16851)
  • Genetics (11399)
  • Genomics (15478)
  • Immunology (10616)
  • Microbiology (25207)
  • Molecular Biology (10220)
  • Neuroscience (54463)
  • Paleontology (401)
  • Pathology (1668)
  • Pharmacology and Toxicology (2897)
  • Physiology (4342)
  • Plant Biology (9243)
  • Scientific Communication and Education (1586)
  • Synthetic Biology (2557)
  • Systems Biology (6780)
  • Zoology (1466)