Abstract
Focal epilepsy originates within networks in one hemisphere. However, previous studies have investigated network topologies for the entire brain. In this study, magnetoencephalography (MEG) was used to investigate functional intra‐hemispheric networks of healthy controls (HCs) and patients with left‐ or right‐hemispheric temporal lobe or temporal plus extra‐temporal lobe epilepsy. 22 HCs, 25 left patients (LPs), and 16 right patients (RPs) were enrolled. The debiased weighted phase lag index was used to calculate functional connectivity between 246 brain regions in six frequency bands. Global efficiency, characteristic path length, and transitivity were computed for left and right intra‐hemispheric networks. The right global graph measures (GGMs) in the theta band were significantly different (p < .005) between RPs and both LPs and HCs. Right and left GGMs in higher frequency bands were significantly different (p < .05) between HCs and the patients. Right GGMs were used as input features of a Naïve‐Bayes classifier to classify LPs and RPs (78.0% accuracy) and all three groups (75.5% accuracy). The complete theta band brain networks were compared between LPs and RPs with network‐based statistics (NBS) and with the clustering coefficient (CC), nodal efficiency (NE), betweenness centrality (BC), and eigenvector centrality (EVC). NBS identified a subnetwork primarily composed of right intra‐hemispheric connections. Significantly different (p < .05) nodes were primarily in the right hemisphere for the CC and NE and primarily in the left hemisphere for the BC and EVC. These results indicate that intra‐hemispheric MEG networks may be incorporated in the diagnosis and lateralization of focal epilepsy.
Highlights
Epilepsy is a chronic brain disorder characterized by recurrent, transient interruptions of normal brain function in the form of hypersynchronous neuronal activity (Fisher et al, 2005)
Because focal epilepsy originates within networks limited to one cerebral hemisphere, using global graph measures to characterize intrahemispheric networks rather than the network of the entire brain may be able to reveal additional information about the brain networks of patients with focal epilepsy
Global graph measures based on functional connectivity (FC) analysis with resting-state MEG (rs-MEG) data were able to distinguish between the intra-hemispheric brain networks of healthy controls (HCs), left patients (LPs), and right patients (RPs), in the theta band
Summary
Epilepsy is a chronic brain disorder characterized by recurrent, transient interruptions of normal brain function in the form of hypersynchronous neuronal activity (Fisher et al, 2005). Many studies have investigated a potential application of local graph measures, those that denote the hub status of a node such as betweenness centrality (BC), in localizing the seizure onset and epileptogenic zones of patients with focal epilepsy to improve outcomes after epilepsy surgery. These localization studies have been performed using effective connectivity analysis with ictal and interictal iEEG (Ren et al, 2019; Wilke, Worrell, & He, 2011) and FC analysis with interictal EEG (Coito et al, 2019) and MEG (Juarez-Martinez et al, 2018; Nissen et al, 2017; Nissen et al, 2018). Network-based statistics (NBS) was used to identify other subnetworks that may be different between LPs and RPs while local graph measures were used to identify brain regions that may have different network properties for LPs and RPs
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