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Neural synchronization is believed to be critical for many brain functions.It frequently exhibits temporal variability, but it is not known if thisvariability has a specific temporal patterning. This study explores thesesynchronization/desynchronization patterns. We employ recently developedtechniques to analyze the fine temporal structure of phase-locking to study thetemporal patterning of synchrony of the human brain rhythms. We study neuraloscillations recorded by EEG in $\alpha$ and $\beta$ frequency bands in healthyhuman subjects at rest and during the execution of a task. While thephase-locking strength depends on many factors, dynamics of synchrony has avery specific temporal pattern: synchronous states are interrupted by frequent,but short desynchronization episodes. The probability for a desynchronizationepisode to occur decreased with its duration. The transition matrix betweensynchronized and desynchronized states has eigenvalues close to 0 and 1 whereeigenvalue 1 has multiplicity 1, and therefore if the stationary distributionbetween these states is perturbed, the system converges back to the stationarydistribution very fast. The qualitative similarity of this patterning acrossdifferent subjects, brain states and electrode locations suggests that this maybe a general type of dynamics for the brain. Earlier studies indicate that notall oscillatory networks have this kind of patterning ofsynchronization/desynchronization dynamics. Thus the observed prevalence ofshort (but potentially frequent) desynchronization events (length of one cycleof oscillations) may have important functional implications for the brain.Numerous short desynchronizations (as opposed to infrequent, but longdesynchronizations) may allow for a quick and efficient formation and break-upof functionally significant neuronal assemblies.

Short desynchronization episodes prevail in synchronous dynamics of human brain rhythms