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Noise during rest enables the exploration of the brain's dynamic repertoire.

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

PLoS Computational Biology October 1, 2008 DOI: 10.1371/journal.pcbi.1000196 (opens in new tab) via PubMed

Summary

AI-generated from the abstract

Resting state networks, which are collections of brain regions showing coordinated activity even when no task is being performed, can emerge from a stability analysis of network dynamics using biologically realistic primate brain connectivity. Anatomical information alone does not identify these networks; noise and time delays from signal propagation along connecting fibers are essential for their emergence. The spatiotemporal dynamics operate on multiple time scales, producing both fast neuroelectric oscillations (1–100 Hz) and slow hemodynamic oscillations (<0.1 Hz). The combination of structure and time delays creates a space-time framework where neural noise allows the brain to explore various functional configurations.

Study at a glance

Characteristics Theoretical or computational analysis Peer reviewed
Key finding Noise and time delays from signal propagation along connecting fibers are essential for the emergence of coherent fluctuations of the default network.

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, <0.1 Hz, observed in functional magnetic resonance imaging. The combination of anatomical structure and time delays creates a space-time structure in which the neural noise enables the brain to explore various functional configurations representing its dynamic repertoire.

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