Graph analysis of resting state EEG functional networks

Migraine is associated with brain dysfunction, possibly due to disturbances in the interactions between distributed cortical regions. Detection of these disturbances in the topological organization of the brain’s functional network would contribute to further understanding of migraine pathophysiology. Altered cortical responses to external stimulation of different modalities are observed in migraine patients, also between attacks (in the interictal state). However, it is yet unclear if abnormalities are detectable in the functional network at rest, i.e. without external stimulation. Here, we assessed abnormalities in migraine functional networks on a global and a local level, based on resting state electroencephalography (EEG) data and graph analysis. Scalp-wide (128-channel)eyes closed EEG was recorded in 18 episodic migraine patients with and withoutaura and 15 healthy controls. We calculated functional connectivity based oncoherence and phase-lag index, and performed graph analysis to characterizenetwork topology. The minimum spanning tree, a subgraph with maximumfunctional connectivity, was used for comparison. No significant differences werefound in network topology, nor in functional connectivity strength between groups. These results demonstrate that this type of graph analyses are not sensitive to any possible abnormalities in the interictal migraine functional network in resting state. Brain dysfunction in migraine might occur only on a local level, making EEG-based graph analysis a less suitable technique to uncover such abnormalities