![]() ![]() To identify the possible presence of these events, we use a new analysis approach based on the Hidden Markov Model (HMM) 21, a general mathematical framework previously used to find recurring states in brain data 22. Here we propose that cortical activity at rest can be described by transient, intermittently reoccurring events in which large-scale networks activate with distinct spectral features that include both power and phase-coupling. However, the evidence for frequency-specific phase-coupling in spontaneous activity at timescales associated with fast cognition is limited. If these spontaneously occurring networks are to provide an effective substrate for cognitive processes, then they might also be expected to exhibit the same fast changing phase-coupling activity observed in tasks 6, 19, 20. These networks have previously been shown to have distinct band-limited power in electroencephalography (EEG) and magnetoencephalography (MEG) 14, 15, 16, 17, 18. Using functional magnetic resonance imaging (fMRI), it has been shown that large-scale networks activated in tasks are also spontaneously recruited in the resting state 13. ![]() The role of phase-coupling at distinct frequencies has also been demonstrated in tasks at the large scale, where task-relevant information is effectively transmitted through phase-locking between separate cortical regions 6, 10, 11, 12. At the same time, phase-coupling between neuronal populations in specific frequency bands has been proposed as a mechanism for regulating the integration and flow of cognitive content 6, 7, 8 and coordinating neuronal spike timing 9. Furthermore, different frequencies, or, more generally, different oscillatory patterns, subserve different functions 5. A proposed mechanism for such coordination is oscillatory synchronisation, that is, populations of neurons transmit information by coordinating their oscillatory activity with the oscillations of the receptor population at certain frequencies. Similar content being viewed by othersĮfficient neuronal coordination between regions across the entire brain is necessary for cognition 1, 2, 3, 4. Our results show that large-scale cortical phase-coupling networks have characteristic signatures in very specific frequency bands, possibly reflecting functional specialisation at different intrinsic timescales. The cognitive networks include a posterior alpha (8–12 Hz) and an anterior delta/theta range (1–7 Hz) network, both exhibiting high power and coherence in areas that correspond to posterior and anterior subdivisions of the default mode network. Brain states are identified for sensory, motor networks and higher-order cognitive networks. We develop a novel method for identifying large-scale phase-coupled network dynamics and show that resting networks in magnetoencephalography are well characterised by visits to short-lived transient brain states, with spatially distinct patterns of oscillatory power and coherence in specific frequency bands. Therefore, the ongoing activity ascribed to the different functional brain networks should also be able to reorganise and coordinate via similar mechanisms. Frequency-specific oscillations and phase-coupling of neuronal populations are essential mechanisms for the coordination of activity between brain areas during cognitive tasks.
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