Exploring mechanisms of spontaneous functional connectivity in MEG: How delayed network interactions lead to structured amplitude envelopes of band-pass filtered oscillations

Spontaneous (or resting-state) brain activity has attracted a growing body of neuroimaging research over the last/ndecades.Whole-brain networkmodels have proved helpful to investigate the source of slow(b0.1 Hz) correlated/nhemodynamic fluctuations revealed in fMRI during rest. However, the mechanisms mediating resting-state/nlong-distance correlations and the relationship with the faster neural activity remain unclear. Novel insights/ncoming from MEG studies have shown that the amplitude envelopes of alpha- and beta-frequency oscillations/n(8–30 Hz) display similar correlation patterns as the fMRI signals./nIn thiswork, we combine experimental and theoreticalwork to investigate the mechanisms of spontaneousMEG/nfunctional connectivity. Using a simple model of coupled oscillators adapted to incorporate realisticwhole-brain/nconnectivity and conduction delays, we explore how slow and structured amplitude envelopes of band-pass/nfiltered signals – fairly reproducing MEG data collected from 10 healthy subjects at rest – are generated spontaneously/nin the space-time structure of the brain network./nOur simulation results show that the large-scale neuroanatomical connectivity provides an optimal network/nstructure to support a regimewith metastable synchronization. In this regime, different subsystems may temporarily/nsynchronize at reduced collective frequencies (falling in the 8–30 Hz range due to the delays) while the/nglobal system never fully synchronizes. This mechanism modulates the frequency of the oscillators on a slow/ntime-scale (b0.1 Hz) leading to structured amplitude fluctuations of band-pass filtered signals. Taken overall,/nour results reveal that the structured amplitude envelope fluctuations observed in resting-state MEG data may/noriginate from spontaneous synchronization mechanisms naturally occurring in the space-time structure of/nthe brain. The research reported herein was supported by the ERC Advanced/nGrant: DYSTRUCTURE (n. 295129), by the FET Flagship Human Brain/nProject, by the Spanish Research Project SAF2010-16085, by the/nCONSOLIDER-INGENIO 2010 CSD2007-00012, by the BrainNRG through/nthe James S. McDonnell Foundation, by the FP7-ICT BrainScales, by the/nRCUK Digital Economy – Centre for Doctoral Training in Healthcare/nInnovation, by theMINDLab Investment Capital for University Research/nFund and by the TrygFonden Charitable Foundation.