School of Life and Health Sciences, Aston Brain Centre, Aston University, Birmingham, UK.
School of Life and Health Sciences, Aston Brain Centre, Aston University, Birmingham, UK; School of Psychology, Faculty of Health, Melbourne Burwood Campus, Deakin University, Geelong, Victoria, Australia.
Neuroimage Clin. 2020;27:102265. doi: 10.1016/j.nicl.2020.102265. Epub 2020 Apr 29.
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.
最近的语言理论模型强调了在语言处理过程中分布式网络内整合的重要性。这对于患有癫痫的年轻患者尤其相关，因为功能性网络的拓扑及其动力学可能因疾病而改变，导致功能性语言网络的重组。因此，了解癫痫患者语言网络中的连通性可以为健康和病理大脑功能提供有价值的见解，特别是与临床相关因素结合时。本研究的目的是使用 MEG 相位同步和图论分析来研究癫痫患者人群中语言网络内的相互作用，并研究它们与语言能力的关系。在 22 名儿科癫痫患者（9 名男性和 13 名女性；平均年龄 14 岁）的动词生成过程中，观察到额颞网络中的连通性增加。在典型和非典型语言表现的患者之间以及语言能力良好和较差的患者之间观察到网络连通性的差异。此外，左额颞区的节点中心度与语言能力显著相关，与语言能力较差的患者相比，语言能力较好的患者在左半球额下回和颞上回的节点中心度明显更高。我们的研究是首次在儿科癫痫中应用基于任务的 MEG 网络同步测量方法，我们提出这些功能连通性和节点中心度的测量方法可以用作在癫痫手术前识别语言网络关键区域的工具。
