Mapping language networks and their association with verbal abilities in paediatric epilepsy using MEG and graph analysis.

Recent theoretical models of language have emphasised the importance of integration within distributed networks during language processing. This is particularly relevant to young patients with epilepsy, as the topology of the functional network and its dynamics may be altered by the disease, resulting in reorganisation of functional language networks. Thus, understanding connectivity within the language network in patients with epilepsy could provide valuable insights into healthy and pathological brain function, particularly when combined with clinical correlates. The objective of this study was to investigate interactions within the language network in a paediatric population of epilepsy patients using measures of MEG phase synchronisation and graph-theoretical analysis, and to examine their association with language abilities. Task dependent increases in connectivity were observed in fronto-temporal networks during verb generation across a group of 22 paediatric patients (9 males and 13 females; mean age 14 years). Differences in network connectivity were observed between patients with typical and atypical language representation and between patients with good and poor language abilities. In addition, node centrality in left frontal and temporal regions was significantly associated with language abilities, where patients with good language abilities had significantly higher node centrality within inferior frontal and superior temporal regions of the left hemisphere, compared to patients with poor language abilities. Our study is one of the first to apply task-based measures of MEG network synchronisation in paediatric epilepsy, and we propose that these measures of functional connectivity and node centrality could be used as tools to identify critical regions of the language network prior to epilepsy surgery.