Model
Digital Document
Publisher
Florida Atlantic University
Description
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. These coherent fluctuations have also been characterized on multiple temporal scales ranging from the fast frequency regimes, 1-100 Hz, commonly observed in EEG and MEG recordings, to the ultra-slow regimes, < 0.1 Hz, observed in the Blood Oxygen Level Dependent (BOLD) signal of functi onal magnetic resonance imaging (fMRI). However, the mechanism for their genesis and the origin of the ultra-slow frequency oscillations has not been well understood. 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 combination of anatomical structure and time delays creates a spacetime structure in which the neural noise enables the brain to explore various functional configurations representing its dynamic repertoire.
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