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Neuroimage. 2014 Apr 15;90:423-35. doi: 10.1016/j.neuroimage.2013.11.047. Epub 2013 Dec 7.

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

Author information

1
Theoretical and Computational Neuroscience Group, Center of Brain and Cognition, Universitat Pompeu Fabra, 08018 Barcelona, Spain; Department of Psychiatry, University of Oxford, OX3 7JX Oxford, UK. Electronic address: joana.cabral@upf.edu.
2
Oxford Centre for Human Brain Activity, University of Oxford, OX3 7JX Oxford, UK; Centre for Doctoral Training in Healthcare Innovation, Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, OX1 3PJ Oxford, UK.
3
Oxford Centre for Human Brain Activity, University of Oxford, OX3 7JX Oxford, UK.
4
Department of Psychiatry, University of Oxford, OX3 7JX Oxford, UK; CFIN/MindLab, Aarhus University, 8000 Aarhus, Denmark.
5
Department of Psychiatry, University of Oxford, OX3 7JX Oxford, UK.
6
Theoretical and Computational Neuroscience Group, Center of Brain and Cognition, Universitat Pompeu Fabra, 08018 Barcelona, Spain; Institució Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain.

Abstract

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.

KEYWORDS:

Functional connectivity; Kuramoto; MEG; Modeling; Network; Oscillations; Resting state; Structural connectivity

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