How do spatially distinct frequency specific MEG networks emerge from one underlying structural connectome? The role of the structural eigenmodes

Functional networks obtained from magnetoencephalography (MEG) from different frequency bands show distinct spatial patterns. It remains to be elucidated how distinct spatial patterns in MEG networks emerge given a single underlying structural network. Recent work has suggested that the eigenmodes o...

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Veröffentlicht in:NeuroImage (Orlando, Fla.) Fla.), 2019-02, Vol.186, p.211-220
Hauptverfasser: Tewarie, Prejaas, Abeysuriya, Romesh, Byrne, Áine, O'Neill, George C., Sotiropoulos, Stamatios N., Brookes, Matthew J., Coombes, Stephen
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Sprache:eng
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Zusammenfassung:Functional networks obtained from magnetoencephalography (MEG) from different frequency bands show distinct spatial patterns. It remains to be elucidated how distinct spatial patterns in MEG networks emerge given a single underlying structural network. Recent work has suggested that the eigenmodes of the structural network might serve as a basis set for functional network patterns in the case of functional MRI. Here, we take this notion further in the context of frequency band specific MEG networks. We show that a selected set of eigenmodes of the structural network can predict different frequency band specific networks in the resting state, ranging from delta (1–4 Hz) to the high gamma band (40–70 Hz). These predictions outperform predictions based from surrogate data, suggesting a genuine relationship between eigenmodes of the structural network and frequency specific MEG networks. We then show that the relevant set of eigenmodes can be excited in a network of neural mass models using linear stability analysis only by including delays. Excitation of an eigenmode in this context refers to a dynamic instability of a network steady state to a spatial pattern with a corresponding coherent temporal oscillation. Simulations verify the results from linear stability analysis and suggest that theta, alpha and beta band networks emerge very near to the bifurcation. The delta and gamma bands in the resting state emerges further away from the bifurcation. These results show for the first time how delayed interactions can excite the relevant set of eigenmodes that give rise to frequency specific functional connectivity patterns. •The first six eigenmodes of the structural network form a basis set for different frequency band specific MEG networks.•Eigenmodes can be excited at the functional network level in a linearised system of neural masses with and without delays.•Offset and axonal delays are required to excite the correct set of eigenmodes at the network bifurcation.•Alpha, Beta and Theta band MEG networks emerge right after the network bifurcation.•Gamma and Delta band MEG networks emerge well after the network bifurcation.
ISSN:1053-8119
1095-9572
DOI:10.1016/j.neuroimage.2018.10.079