Ongoing Cortical Activity at Rest: Criticality, Multistability, and Ghost Attractors

The brain's ongoing activity at rest, in the absence of tasks or stimulation, is highly structured into spatiotemporal patterns known as resting state networks, which exhibit low-frequency fluctuations below 0.1 Hz. Using a global spiking attractor network model that incorporates realistic neuroanatomical connectivity from diffusion tensor imaging, the authors demonstrate that resting state functional connectivity quantitatively matches human experimental data when the brain network operates at the edge of instability. Under these conditions, slow fluctuations emerge as structured noise around a stable low firing equilibrium, shaped by latent multistable attractors inherent in the neuroanatomical connectivity.

Study at a glance

Abstract

The ongoing activity of the brain at rest, i.e., under no stimulation and in absence of any task, is astonishingly highly structured into spatiotemporal patterns. These spatiotemporal patterns, called resting state networks, display low-frequency characteristics (<0.1 Hz) observed typically in the BOLD-fMRI signal of human subjects. We aim here to understand the origins of resting state activity through modeling via a global spiking attractor network of the brain. This approach offers a realistic mechanistic model at the level of each single brain area based on spiking neurons and realistic AMPA, NMDA, and GABA synapses. Integrating the biologically realistic diffusion tensor imaging/diffusion spectrum imaging-based neuroanatomical connectivity into the brain model, the resultant emerging resting state functional connectivity of the brain network fits quantitatively best the experimentally observed functional connectivity in humans when the brain network operates at the edge of instability. Under these conditions, the slow fluctuating (<0.1 Hz) resting state networks emerge as structured noise fluctuations around a stable low firing activity equilibrium state in the presence of latent "ghost" multistable attractors. The multistable attractor landscape defines a functionally meaningful dynamic repertoire of the brain network that is inherently present in the neuroanatomical connectivity.