  Neural synchronization is believed to be critical for many brain functions.
It frequently exhibits temporal variability, but it is not known if this
variability has a specific temporal patterning. This study explores these
synchronization/desynchronization patterns. We employ recently developed
techniques to analyze the fine temporal structure of phase-locking to study the
temporal patterning of synchrony of the human brain rhythms. We study neural
oscillations recorded by EEG in $\alpha$ and $\beta$ frequency bands in healthy
human subjects at rest and during the execution of a task. While the
phase-locking strength depends on many factors, dynamics of synchrony has a
very specific temporal pattern: synchronous states are interrupted by frequent,
but short desynchronization episodes. The probability for a desynchronization
episode to occur decreased with its duration. The transition matrix between
synchronized and desynchronized states has eigenvalues close to 0 and 1 where
eigenvalue 1 has multiplicity 1, and therefore if the stationary distribution
between these states is perturbed, the system converges back to the stationary
distribution very fast. The qualitative similarity of this patterning across
different subjects, brain states and electrode locations suggests that this may
be a general type of dynamics for the brain. Earlier studies indicate that not
all oscillatory networks have this kind of patterning of
synchronization/desynchronization dynamics. Thus the observed prevalence of
short (but potentially frequent) desynchronization events (length of one cycle
of oscillations) may have important functional implications for the brain.
Numerous short desynchronizations (as opposed to infrequent, but long
desynchronizations) may allow for a quick and efficient formation and break-up
of functionally significant neuronal assemblies.

Neurons and Cognition;Adaptation and Self-Organizing Systems