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

Journal article

Spontaneous (or resting-state) brain activity has attracted a growing body of neuroimaging research over the last decades. Whole-brain network models have proved helpful to investigate the source of slow (<0.1 Hz) correlated hemodynamic fluctuations revealed in fMRI during rest. However, the mechanisms mediating resting-state long-distance correlations and the relationship with the faster neural activity remain unclear. Novel insights coming from MEG studies have shown that the amplitude envelopes of alpha- and beta-frequency oscillations (~8-30 Hz) display similar correlation patterns as the fMRI signals. In this work, we combine experimental and theoretical work to investigate the mechanisms of spontaneous MEG functional connectivity. Using a simple model of coupled oscillators adapted to incorporate realistic whole-brain connectivity and conduction delays, we explore how slow and structured amplitude envelopes of band-pass filtered signals - fairly reproducing MEG data collected from 10 healthy subjects at rest - are generated spontaneously in the space-time structure of the brain network. Our simulation results show that the large-scale neuroanatomical connectivity provides an optimal network structure to support a regime with metastable synchronization. In this regime, different subsystems may temporarily synchronize at reduced collective frequencies (falling in the 8-30 Hz range due to the delays) while the global system never fully synchronizes. This mechanism modulates the frequency of the oscillators on a slow time-scale (<0.1 Hz) leading to structured amplitude fluctuations of band-pass filtered signals. Taken overall, our results reveal that the structured amplitude envelope fluctuations observed in resting-state MEG data may originate from spontaneous synchronization mechanisms naturally occurring in the space-time structure of the brain.

Authors: Cabral, J; Luckhoo, H; Woolrich, M; Joensson, M; Mohseni, H

• Publication status: Published
• Journal: NeuroImage
• Volume: 90
• Pages: 423-435
• Publication date: 2014-04-01
• DOI: 10.1016/j.neuroimage.2013.11.047
• EISSN: 1095-9572
• ISSN: 1053-8119
• Language: English
• Keywords: Nerve Net; Young Adult; Brain Mapping; Brain; Humans; Rest; Magnetoencephalography; Adult; Female; Male; Signal Processing, Computer-Assisted; Neural Pathways