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.
Highlights
When subjects are not actively engaged in goal-directed mental activity, spontaneous brain activity has been suggested not to represent ‘‘noise’’, but rather implicate spontaneous and transient processes involved in task-unrelated imagery and thought [1,2,3,4,5,6,7,8,9]
Most hypotheses on the underlying mechanisms of rest state dynamics in the EEG/MEG consider alpha wave generation and postulate either of two hypotheses: pacemaker oscillators in the thalamus or cortex generate rhythms endogenously, which entrain the remainder of the cortex [12,13]
In a computational study using a biologically realistic primate cortical connectivity matrix, we show that the rest state networks emerge only if the time delays of signal transmission between brain areas are considered
Summary
When subjects are not actively engaged in goal-directed mental activity, spontaneous brain activity has been suggested not to represent ‘‘noise’’, but rather implicate spontaneous and transient processes involved in task-unrelated imagery and thought [1,2,3,4,5,6,7,8,9]. The assumption of a link between resting state activity and mental processes is founded largely ‘‘ex negativo’’ upon Positron Emission Tomography (PET) and fMRI studies showing the deactivation of the ‘‘default-mode’’ network in correlation with the increase in task-related activity in sensory-driven areas during goal-directed behavior The dynamics of these spontaneous fluctuations evolves on a slow time scale of multiple seconds. The neuronal network may either act as a narrow band transmission system (i.e., as a filter originally proposed by Prast in 1949 [14]) receiving white noise as input and producing the irregular rhythms; or the neural network generates a purely deterministic, often chaotic, signal reflecting the dynamics of coupled nonlinear oscillators [15,16,17,18,19] All these computational models have some experimental support, but in general are too vague to pinpoint specific mechanisms.
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