Abstracts

Rationale: Resting-state functional connectivity and network analysis in electroencephalogram (EEG) and magnetoencephalogram (MEG) data are increasingly being used to elucidate the fundamental pathogenesis of Idiopathic Generalised Epilepsies (IGE). However, case-control studies have revealed little consensus in results, in the context of a rapidly expanding array of methodologies and analysis techniques available. The aim of this review is to establish the differences in inter-ictal resting-state functional connectivity between IGE patients and healthy controls and to provide a synthesis of the current literature. Methods: The systematic review was conducted according to PRISMA guidelines. The protocol was registered with the international Prospective Register of Systematic Reviews (PROSPERO registration number: CRD42017046961). Scopus and Medline (Ovid) databases were searched for relevant studies from January 2000 to December 2017. Search terms included “Idiopathic generalised epilepsy” AND “functional connectivity” OR “graph theory” AND “EEG” OR “MEG”. Studies were limited to full-text, human case control studies which assessed inter-ictal periods. Only studies in English were included. The title and abstract of each study was reviewed for eligibility, before an assessment of study quality and bias was conducted. Results: A total of 296 studies were identified by the search criteria, with 16 studies meeting criteria for full-text review. The mean age of IGE patients across the studies was 18.6 years. Several studies (n=6) used an unmedicated or drug naïve sample, others used a mix of mono-or poly therapy. Most studies used EEG as the recording modality (n=11), as opposed to MEG. Non-directed measures of functional connectivity were largely utilised, with a mixture of linear and non-linear approaches. A trend for increased connectivity in people with IGE was observed, most notable in the higher frequency bands (13-80Hz). Approximately half of the assessed studies (n=9) used graph theory metrics to further characterise network properties, with results showing a mix of increased global efficiency or no difference in topographies relative to controls. Conclusions: Resting-state functional connectivity and network analysis is an exciting and rapidly evolving tool to assess disease states. Network analysis in IGE is still in its infancy and substantial heterogeneity across methodologies and techniques exists. Nonetheless, the review suggests there is evidence for hyper-connectivity in IGE, even outside of ictal phases. These findings highlight the importance of developing standardised validated methodologies and the need to ground these measures in validated multimodal correlates and clinical outcomes. Funding: None