The structural connectome constrains fast brain dynamics

  1. Pierpaolo Sorrentino  Is a corresponding author
  2. Caio Seguin
  3. Rosaria Rucco
  4. Marianna Liparoti
  5. Emahnuel Troisi Lopez
  6. Simona Bonavita
  7. Mario Quarantelli MD
  8. Giuseppe Sorrentino
  9. Viktor Jirsa
  10. Andrew Zalesky
  1. Aix-Marseille University, France
  2. University of Melbourne, Australia
  3. University of Naples Parthenope"", Italy
  4. Parthenope University of Naples, Italy
  5. university of Campania Muigi Vanvitelli, Italy
  6. National Research Council, Italy
  7. Aix-Marseille Université, France
  8. The University of Melbourne, Australia

Abstract

Brain activity during rest displays complex, rapidly evolving patterns in space and time. Structural connections comprising the human connectome are hypothesized to impose constraints on the dynamics of this activity. Here, we use magnetoencephalography (MEG) to quantify the extent to which fast neural dynamics in the human brain are constrained by structural connections inferred from diffusion MRI tractography. We characterize the spatio-temporal unfolding of whole-brain activity at the millisecond scale from source-reconstructed MEG data, estimating the probability that any two brain regions will significantly deviate from baseline activity in consecutive time epochs. We find that the structural connectome relates to, and likely affects, the rapid spreading of neuronal avalanches, evidenced by a significant association between these transition probabilities and structural connectivity strengths (r=0.37, <0.0001). This finding opens new avenues to study the relationship between brain structure and neural dynamics.

Data availability

The MEG data and the reconstructed avalanches are available upon request to the corresponding author (Pierpaolo Sorrentino), conditional on appropriate ethics approval at the local site. The availability of the data was not previously included in the ethical approval, and therefore data cannot be shared directly. In case data are requested, the corresponding author will request an amendment to the local ethical committee. Conditional to approval, the data will be made available. The Matlab code is available at https://github.com/pierpaolosorrentino/Transition-Matrices-

Article and author information

Author details

  1. Pierpaolo Sorrentino

    Institut de Neurosciences des Systèmes, Aix-Marseille University, Marseille, France
    For correspondence
    pierpaolo.SORRENTINO@univ-amu.fr
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9556-9800
  2. Caio Seguin

    University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  3. Rosaria Rucco

    Department of Motor Sciences and Wellness, University of Naples Parthenope"", Naples, Italy
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0943-131X
  4. Marianna Liparoti

    scienze motorie, Parthenope University of Naples, Naples, Italy
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2192-6841
  5. Emahnuel Troisi Lopez

    scienze motorie, Parthenope University of Naples, Naples, Italy
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0220-2672
  6. Simona Bonavita

    Neurology Unit, university of Campania Muigi Vanvitelli, Naples, Italy
    Competing interests
    The authors declare that no competing interests exist.
  7. Mario Quarantelli MD

    Biostructure and Bioimaging Institute, National Research Council, Naples, Italy
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7836-454X
  8. Giuseppe Sorrentino

    Department of Motor Science and Wellness, University of Naples Parthenope"", Naples, Italy
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0800-2433
  9. Viktor Jirsa

    Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8251-8860
  10. Andrew Zalesky

    Melbourne Neuropsychiatry Centre, The University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.

Funding

No external funding was received for this work.

Ethics

Human subjects: All participants gave written informed consent. The study complied with the declaration of Helsinki and was approved by the local Ethics Committee (Prot.n.93C.E./Reg. n.14-17OSS).

Copyright

© 2021, Sorrentino et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 2,126
    views
  • 305
    downloads
  • 58
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Pierpaolo Sorrentino
  2. Caio Seguin
  3. Rosaria Rucco
  4. Marianna Liparoti
  5. Emahnuel Troisi Lopez
  6. Simona Bonavita
  7. Mario Quarantelli MD
  8. Giuseppe Sorrentino
  9. Viktor Jirsa
  10. Andrew Zalesky
(2021)
The structural connectome constrains fast brain dynamics
eLife 10:e67400.
https://doi.org/10.7554/eLife.67400

Share this article

https://doi.org/10.7554/eLife.67400

Further reading

    1. Cell Biology
    2. Computational and Systems Biology
    Trine Line Hauge Okholm, Andreas Bjerregaard Kamstrup ... Christian Kroun Damgaard
    Research Article

    Circular RNAs represent a class of endogenous RNAs that regulate gene expression and influence cell biological decisions with implications for the pathogenesis of several diseases. Here, we disclose a novel gene-regulatory role of circHIPK3 by combining analyses of large genomics datasets and mechanistic cell biological follow-up experiments. Using time-course depletion of circHIPK3 and specific candidate RNA-binding proteins, we identify several perturbed genes by RNA sequencing analyses. Expression-coupled motif analyses identify an 11-mer motif within circHIPK3, which also becomes enriched in genes that are downregulated upon circHIPK3 depletion. By mining eCLIP datasets and combined with RNA immunoprecipitation assays, we demonstrate that the 11-mer motif constitutes a strong binding site for IGF2BP2 in bladder cancer cell lines. Our results suggest that circHIPK3 can sequester IGF2BP2 as a competing endogenous RNA (ceRNA), leading to target mRNA stabilization. As an example of a circHIPK3-regulated gene, we focus on the STAT3 mRNA as a specific substrate of IGF2BP2 and validate that manipulation of circHIPK3 regulates IGF2BP2-STAT3 mRNA binding and, thereby, STAT3 mRNA levels. Surprisingly, absolute copy number quantifications demonstrate that IGF2BP2 outnumbers circHIPK3 by orders of magnitude, which is inconsistent with a simple 1:1 ceRNA hypothesis. Instead, we show that circHIPK3 can nucleate multiple copies of IGF2BP2, potentially via phase separation, to produce IGF2BP2 condensates. Our results support a model where a few cellular circHIPK3 molecules can induce IGF2BP2 condensation, thereby regulating key factors for cell proliferation.

    1. Cell Biology
    2. Computational and Systems Biology
    N Suhas Jagannathan, Javier Yu Peng Koh ... Lisa Tucker-Kellogg
    Research Article

    Bats have unique characteristics compared to other mammals, including increased longevity and higher resistance to cancer and infectious disease. While previous studies have analyzed the metabolic requirements for flight, it is still unclear how bat metabolism supports these unique features, and no study has integrated metabolomics, transcriptomics, and proteomics to characterize bat metabolism. In this work, we performed a multi-omics data analysis using a computational model of metabolic fluxes to identify fundamental differences in central metabolism between primary lung fibroblast cell lines from the black flying fox fruit bat (Pteropus alecto) and human. Bat cells showed higher expression levels of Complex I components of electron transport chain (ETC), but, remarkably, a lower rate of oxygen consumption. Computational modeling interpreted these results as indicating that Complex II activity may be low or reversed, similar to an ischemic state. An ischemic-like state of bats was also supported by decreased levels of central metabolites and increased ratios of succinate to fumarate in bat cells. Ischemic states tend to produce reactive oxygen species (ROS), which would be incompatible with the longevity of bats. However, bat cells had higher antioxidant reservoirs (higher total glutathione and higher ratio of NADPH to NADP) despite higher mitochondrial ROS levels. In addition, bat cells were more resistant to glucose deprivation and had increased resistance to ferroptosis, one of the characteristics of which is oxidative stress. Thus, our studies revealed distinct differences in the ETC regulation and metabolic stress responses between human and bat cells.