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Noise during Rest Enables the Exploration of the Brain's Dynamic Repertoire

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  • Anandamohan Ghosh
  • Y Rho
  • A R McIntosh
  • R Kötter
  • V K Jirsa

Abstract

Traditionally brain function is studied through measuring physiological responses in controlled sensory, motor, and cognitive paradigms. However, even at rest, in the absence of overt goal-directed behavior, collections of cortical regions consistently show temporally coherent activity. In humans, these resting state networks have been shown to greatly overlap with functional architectures present during consciously directed activity, which motivates the interpretation of rest activity as day dreaming, free association, stream of consciousness, and inner rehearsal. In monkeys, it has been shown though that similar coherent fluctuations are present during deep anesthesia when there is no consciousness. Here, we show that comparable resting state networks emerge from a stability analysis of the network dynamics using biologically realistic primate brain connectivity, although anatomical information alone does not identify the network. We specifically demonstrate that noise and time delays via propagation along connecting fibres are essential for the emergence of the coherent fluctuations of the default network. The spatiotemporal network dynamics evolves on multiple temporal scales and displays the intermittent neuroelectric oscillations in the fast frequency regimes, 1–100 Hz, commonly observed in electroencephalographic and magnetoencephalographic recordings, as well as the hemodynamic oscillations in the ultraslow regimes,

Suggested Citation

  • Anandamohan Ghosh & Y Rho & A R McIntosh & R Kötter & V K Jirsa, 2008. "Noise during Rest Enables the Exploration of the Brain's Dynamic Repertoire," PLOS Computational Biology, Public Library of Science, vol. 4(10), pages 1-12, October.
  • Handle: RePEc:plo:pcbi00:1000196
    DOI: 10.1371/journal.pcbi.1000196
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    References listed on IDEAS

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    1. J. L. Vincent & G. H. Patel & M. D. Fox & A. Z. Snyder & J. T. Baker & D. C. Van Essen & J. M. Zempel & L. H. Snyder & M. Corbetta & M. E. Raichle, 2007. "Intrinsic functional architecture in the anaesthetized monkey brain," Nature, Nature, vol. 447(7140), pages 83-86, May.
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    1. Robert Ton & Gustavo Deco & Andreas Daffertshofer, 2014. "Structure-Function Discrepancy: Inhomogeneity and Delays in Synchronized Neural Networks," PLOS Computational Biology, Public Library of Science, vol. 10(7), pages 1-15, July.
    2. Ang Li & Haiyang Liu & Xu Lei & Yini He & Qian Wu & Yan Yan & Xin Zhou & Xiaohan Tian & Yingjie Peng & Shangzheng Huang & Kaixin Li & Meng Wang & Yuqing Sun & Hao Yan & Cheng Zhang & Sheng He & Ruquan, 2023. "Hierarchical fluctuation shapes a dynamic flow linked to states of consciousness," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
    3. Klaas Enno Stephan & Anthony Randal McIntosh & Claus C Hilgetag, 2010. "In Memoriam: Rolf Kötter (1961–2010)," PLOS Computational Biology, Public Library of Science, vol. 6(10), pages 1-3, October.
    4. Viktor Sip & Meysam Hashemi & Anirudh N Vattikonda & Marmaduke M Woodman & Huifang Wang & Julia Scholly & Samuel Medina Villalon & Maxime Guye & Fabrice Bartolomei & Viktor K Jirsa, 2021. "Data-driven method to infer the seizure propagation patterns in an epileptic brain from intracranial electroencephalography," PLOS Computational Biology, Public Library of Science, vol. 17(2), pages 1-31, February.

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