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

TLDR

Resting‑state networks exhibit temporally coherent activity that overlaps with task‑related functional architectures and persists even under deep anesthesia, suggesting that rest activity reflects intrinsic brain dynamics. The study demonstrates that such resting‑state networks can be derived from a stability analysis of biologically realistic primate brain connectivity, revealing that anatomical structure alone is insufficient to identify them. The authors show that neural noise and propagation delays along fiber tracts are essential for generating the coherent fluctuations of the default network. The model reproduces multiscale spatiotemporal dynamics—fast 1–100 Hz oscillations and slow <0.1 Hz hemodynamic fluctuations—and demonstrates that the combination of anatomical connectivity, time delays, and noise enables the brain to explore a diverse functional repertoire.

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.