Key role of coupling, delay, and noise in resting brain fluctuations

TLDR

Resting‑state neuroimaging shows temporally coherent activity in the default‑mode network, linked to daydreaming and inner rehearsal, and its complex yet consistent spatiotemporal patterns raise the question of whether they reflect cognitive architecture or intrinsic network constraints. We simulated a simplified cortical network of 38 noise‑driven Wilson‑Cowan oscillators, each just below its oscillatory threshold, to study how delay‑based coupling shapes network dynamics. Delay‑coupled oscillators produced two sets of 40‑Hz rhythms that anticorrelated below 0.1 Hz, with synchrony and simulated BOLD highly sensitive to conduction velocity, coupling strength, and noise, peaking at 1–2 m/s and weak coupling and exhibiting stochastic resonance at an optimal noise level.

Abstract

A growing body of neuroimaging research has documented that, in the absence of an explicit task, the brain shows temporally coherent activity. This so-called "resting state" activity or, more explicitly, the default-mode network, has been associated with daydreaming, free association, stream of consciousness, or inner rehearsal in humans, but similar patterns have also been found under anesthesia and in monkeys. Spatiotemporal activity patterns in the default-mode network are both complex and consistent, which raises the question whether they are the expression of an interesting cognitive architecture or the consequence of intrinsic network constraints. In numerical simulation, we studied the dynamics of a simplified cortical network using 38 noise-driven (Wilson-Cowan) oscillators, which in isolation remain just below their oscillatory threshold. Time delay coupling based on lengths and strengths of primate corticocortical pathways leads to the emergence of 2 sets of 40-Hz oscillators. The sets showed synchronization that was anticorrelated at <0.1 Hz across the sets in line with a wide range of recent experimental observations. Systematic variation of conduction velocity, coupling strength, and noise level indicate a high sensitivity of emerging synchrony as well as simulated blood flow blood oxygen level-dependent (BOLD) on the underlying parameter values. Optimal sensitivity was observed around conduction velocities of 1-2 m/s, with very weak coupling between oscillators. An additional finding was that the optimal noise level had a characteristic scale, indicating the presence of stochastic resonance, which allows the network dynamics to respond with high sensitivity to changes in diffuse feedback activity.