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

Transitions in brain-network level information processing dynamics are driven by alterations in neural gain

View ORCID ProfileMike Li, View ORCID ProfileYinuo Han, Matthew J. Aburn, Michael Breakspear, Russell A. Poldrack, James M. Shine, View ORCID ProfileJoseph T. Lizier
doi: https://doi.org/10.1101/581538
Mike Li
1Centre for Complex Systems, The University of Sydney, Sydney, Australia
2Brain and Mind Centre, The University of Sydney, Sydney. Australia
3Complex Systems Research Group, Faculty of Engineering and IT, The University of Sydney, Sydney, Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Mike Li
Yinuo Han
1Centre for Complex Systems, The University of Sydney, Sydney, Australia
2Brain and Mind Centre, The University of Sydney, Sydney. Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Yinuo Han
Matthew J. Aburn
4QIMR Berghofer Medical Research Institute, Queensland, Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Michael Breakspear
4QIMR Berghofer Medical Research Institute, Queensland, Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Russell A. Poldrack
5Department of Psychology, Stanford University, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
James M. Shine
1Centre for Complex Systems, The University of Sydney, Sydney, Australia
2Brain and Mind Centre, The University of Sydney, Sydney. Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Joseph T. Lizier
1Centre for Complex Systems, The University of Sydney, Sydney, Australia
3Complex Systems Research Group, Faculty of Engineering and IT, The University of Sydney, Sydney, Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Joseph T. Lizier
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

A key component of the flexibility and complexity of the brain is its ability to dynamically adapt its functional network structure between integrated and segregated brain states depending on the demands of different cognitive tasks. Integrated states are prevalent when performing tasks of high complexity, such as maintaining items in working memory, consistent with models of a global workspace architecture. Recent work has suggested that the balance between integration and segregation is under the control of ascending neuromodulatory systems, such as the noradrenergic system. In a previous large-scale nonlinear oscillator model of neuronal network dynamics, we showed that manipulating neural gain led to a ‘critical’ transition in phase synchrony that was associated with a shift from segregated to integrated topology, thus confirming our original prediction. In this study, we advance these results by demonstrating that the gain-mediated phase transition is characterized by a shift in the underlying dynamics of neural information processing. Specifically, the dynamics of the subcritical (segregated) regime are dominated by information storage, whereas the supercritical (integrated) regime is associated with increased information transfer (measured via transfer entropy). Operating near to the critical regime with respect to modulating neural gain would thus appear to provide computational advantages, offering flexibility in the information processing that can be performed with only subtle changes in gain control. Our results thus link studies of whole-brain network topology and the ascending arousal system with information processing dynamics, and suggest that the constraints imposed by the ascending arousal system constrain low-dimensional modes of information processing within the brain.

Author summary Higher brain function relies on a dynamic balance between functional integration and segregation. Previous work has shown that this balance is mediated in part by alterations in neural gain, which are thought to relate to projections from ascending neuromodulatory nuclei, such as the locus coeruleus. Here, we extend this work by demonstrating that the modulation of neural gain alters the information processing dynamics of the neural components of a biophysical neural model. Specifically, we find that low levels of neural gain are characterized by high Active Information Storage, whereas higher levels of neural gain are associated with an increase in inter-regional Transfer Entropy. Our results suggest that the modulation of neural gain via the ascending arousal system may fundamentally alter the information processing mode of the brain, which in turn has important implications for understanding the biophysical basis of cognition.

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 4.0 International license.
Back to top
PreviousNext
Posted March 19, 2019.
Download PDF
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.
Transitions in brain-network level information processing dynamics are driven by alterations in neural gain
(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
Transitions in brain-network level information processing dynamics are driven by alterations in neural gain
Mike Li, Yinuo Han, Matthew J. Aburn, Michael Breakspear, Russell A. Poldrack, James M. Shine, Joseph T. Lizier
bioRxiv 581538; doi: https://doi.org/10.1101/581538
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
Transitions in brain-network level information processing dynamics are driven by alterations in neural gain
Mike Li, Yinuo Han, Matthew J. Aburn, Michael Breakspear, Russell A. Poldrack, James M. Shine, Joseph T. Lizier
bioRxiv 581538; doi: https://doi.org/10.1101/581538

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 (2410)
  • Biochemistry (4765)
  • Bioengineering (3310)
  • Bioinformatics (14607)
  • Biophysics (6600)
  • Cancer Biology (5144)
  • Cell Biology (7389)
  • Clinical Trials (138)
  • Developmental Biology (4330)
  • Ecology (6841)
  • Epidemiology (2057)
  • Evolutionary Biology (9860)
  • Genetics (7322)
  • Genomics (9483)
  • Immunology (4517)
  • Microbiology (12615)
  • Molecular Biology (4909)
  • Neuroscience (28173)
  • Paleontology (198)
  • Pathology (800)
  • Pharmacology and Toxicology (1375)
  • Physiology (2005)
  • Plant Biology (4461)
  • Scientific Communication and Education (973)
  • Synthetic Biology (1295)
  • Systems Biology (3898)
  • Zoology (719)