Integrating cross-frequency and within band functional networks in resting-state MEG: A multi-layer network approach

Abstract

Neuronal oscillations exist across a broad frequency spectrum, and are thought to provide a mechanism of interaction between spatially separated brain regions. Since ongoing mental activity necessitates the simultaneous formation of multiple networks, it seems likely that the brain employs interactions within multiple frequency bands, as well as cross-frequency coupling, to support such networks. Here, we propose a multi-layer network framework that elucidates this pan-spectral picture of network interactions. Our network consists of multiple layers (frequency-band specific networks) that influence each other via inter-layer (cross-frequency) coupling. Applying this model to MEG resting-state data and using envelope correlations as connectivity metric, we demonstrate strong dependency between within layer structure and inter-layer coupling, indicating that networks obtained in different frequency bands do not act as independent entities. More specifically, our results suggest that frequency band specific networks are characterised by a common structure seen across all layers, superimposed by layer specific connectivity, and inter-layer coupling is most strongly associated with this common mode. Finally, using a biophysical model, we demonstrate that there are two regimes of multi-layer network behaviour; one in which different layers are independent and a second in which they operate highly dependent. Results suggest that the healthy human brain operates at the transition point between these regimes, allowing for integration and segregation between layers. Overall, our observations show that a complete picture of global brain network connectivity requires integration of connectivity patterns across the full frequency spectrum.

Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology

“…As mentioned above, fMRI studies have shown that, in the absence of task demand, the resting brain exhibits spontaneous and highly structured, often oscillatory, fluctuations in activity [389]. MEG and EEG provide a richer view of these networks in the time and frequency domains [390–395]. Resting state networks are usually studied using time-frequency decomposition of MEG (or EEG) signals.…”

Multilayer modeling and analysis of human brain networks

“…Two regimes of multilayer network behavior have been identified in a system with five layers (bands 1–4, 4–8, 8–13, 13–30, and 30–48 Hz): in the first regime, layers are independent, while in the second regime they are highly dependent. Results suggest that the healthy human brain operates at the transition point between these two regimes [37]. …”

Applications of Resting State Functional MR Imaging to Traumatic Brain Injury

“…In addition, the number of cortical regions with abnormal delta waves correlated significantly with the post-concussive symptom scores. 49–52 Preliminary data from another study also showed coup-contrecoup injury patterns.…”