  During slow-wave sleep, the brain is in a self-organized regime in which slow
oscillations (SOs) between up- and down-states travel across the cortex. While
an isolated piece of cortex can produce SOs, the brain-wide propagation of
these oscillations are thought to be mediated by the long-range axonal
connections. We address the mechanism of how SOs emerge and recruit large parts
of the brain using a whole-brain model constructed from empirical connectivity
data in which SOs are induced independently in each brain area by a local
adaptation mechanism. Using an evolutionary optimization approach, good fits to
human resting-state fMRI data and sleep EEG data are found at values of the
adaptation strength close to a bifurcation where the model produces a balance
between local and global SOs with realistic spatiotemporal statistics. Local
oscillations are more frequent, last shorter, and have a lower amplitude.
Global oscillations spread as waves of silence across the brain, traveling from
anterior to posterior regions. These traveling waves are caused by
heterogeneities in the brain network in which the connection strengths between
brain areas determine which areas transition to a down-state first, and thus
initiate traveling waves across the cortex. Our results demonstrate the utility
of whole-brain models for explaining the origin of large-scale cortical
oscillations and how they are shaped by the connectome.
