Single or multiple frequency generators in on-going brain activity: A mechanistic whole-brain model of empirical MEG data

Gustavo Deco,Joana Cabral,Mark W Woolrich,Angus B.A Stevner,Tim J Van Hartevelt,Morten L Kringelbach

doi:10.1016/j.neuroimage.2017.03.023

Abstract

During rest, envelopes of band-limited on-going MEG signals co-vary across the brain in consistent patterns, which have been related to resting-state networks measured with fMRI. To investigate the genesis of such envelope correlations, we consider a whole-brain network model assuming two distinct fundamental scenarios: one where each brain area generates oscillations in a single frequency, and a novel one where each brain area can generate oscillations in multiple frequency bands. The models share, as a common generator of damped oscillations, the normal form of a supercritical Hopf bifurcation operating at the critical border between the steady state and the oscillatory regime. The envelopes of the simulated signals are compared with empirical MEG data using new methods to analyse the envelope dynamics in terms of their phase coherence and stability across the spectrum of carrier frequencies.Considering the whole-brain model with a single frequency generator in each brain area, we obtain the best fit with the empirical MEG data when the fundamental frequency is tuned at 12Hz. However, when multiple frequency generators are placed at each local brain area, we obtain an improved fit of the spatio-temporal structure of on-going MEG data across all frequency bands. Our results indicate that the brain is likely to operate on multiple frequency channels during rest, introducing a novel dimension for future models of large-scale brain activity.

Highlights

Understanding the genesis of spatially and temporally structured brain rhythms is a crucial matter in neuroscience (Buzsáki, 2006; Wang, 2010; Womelsdorf et al, 2014)
In order to emulate the global characteristics of spontaneous wholebrain dynamics observed in empirical MEG data from a group of healthy humans we used a whole-brain model linking the underlying anatomical structural connectivity with the local dynamics of each brain area
In order to visualize the similarity between simulations and empirical resting-state data for the carrier band centred at fcarrier=12 Hz, we report in Fig. 7C the corresponding Envelope functional connectivity (FC) matrices, the Connectivity Dynamics (CCD) matrices, CCD distributions and the evolution of the Envelope Synchronization over time (defined in Eq (7))

Summary

Introduction

Understanding the genesis of spatially and temporally structured brain rhythms is a crucial matter in neuroscience (Buzsáki, 2006; Wang, 2010; Womelsdorf et al, 2014). The ratio of time scales of excitatory and inhibitory currents and the balance between excitation and inhibition affect the properties of the rhythms To investigate how these locally generated oscillations interact at the macroscopic level of the whole brain network, it is useful to use neural-mass models in order to reduce the complexity of spiking neuron models to a small set of differential equations describing the population activity (Honey et al, 2007; Ghosh et al, 2008; Deco et al, 2009; Cabral et al, 2011; Cabral et al, 2014a). These models have proved useful to investigate the source of long-range slow BOLD signal correlations, they assume a homogeneous oscillation frequency in every brain area, whereas evidence from EEG and MEG studies points in a different direction, i.e. that brain functional connectivity (FC) occurs in multiple frequency levels, displaying different functional networks according to the carrier oscillations (Mantini et al, 2007; de Pasquale et al, 2010; Brookes et al, 2011b; Hipp et al, 2012; Magri et al, 2012; Tagliazucchi et al, 2012; Keller et al, 2013; Hipp and Siegel, 2015)

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