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

By Joana Cabral, Henry Luckhoo, Mark William Woolrich, Morten Joensson, Hamid Reza Mohseni, Adam P. Baker, Morten L. Kringelbach, Gustavo Deco. NeuroImage, 2014

299 citations recorded by the source corpus.

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.

Subfields: Cognitive Neuroscience, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/3e92ddefa41b5cb4ba3527b804d9b7acbccbed80

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

In Computer Networks and Communications

Citations in the corpus

Mathematical framework for large-scale brain network modeling in The Virtual Brain (2015, unknown): “…also linearly scaled by a factor a, the ratio between a model parameter C and the node's in-strength (Alstott et al., 2009; Honey et al., 2007), the number of nodes in the network (Kuramoto, 1975; Cabral et al., 2014a; Daffertshofer and van Wijk, 2011), or the in-degree if the matrix U is binary.”
Functional connectivity dynamically evolves on multiple time-scales over a static structural connectome: Models and mechanisms (2017, methodology): “In Deco et al. (2016a), a range of natural frequencies between 2 and 30Hz was tested with the Hopf model, finding the best agreement with MEG-based envelope FC matrices for an intrinsic frequency at 12Hz.”
Coupling functions:universal insights into dynamical interaction mechanisms (2017, background): “…model is the cornerstone for many studies and applications (Acebrón et al., 2005; Strogatz, 2000), including neuroscience (Breakspear et al., 2010; Cabral et al., 2014; Cumin and Unsworth, 2007), Josephsonjunction arrays (Filatrella et al., 2000; Wiesenfeld et al., 1996, 1998), power grids…”