Introduction: How components of the distributed brain networks that support cognition participate in typical functioning remains a largely unanswered question. An important subgroup of regions in the larger network are connector hubs, which are areas that are highly connected to several other functionally specialized sets of regions, and are likely important for sensorimotor integration. The present study attempts to characterize connector hubs involved in typical expressive language functioning using a data-driven, multimodal, full multilayer magnetoencephalography (MEG) connectivity-based pipeline.

中文翻译：

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多层连接器集线器映射揭示了支持表达语言的关键大脑区域

简介：支持认知的分布式大脑网络的组件如何参与典型功能仍然是一个很大程度上未解决的问题。较大网络中一个重要的区域子组是连接器集线器，这些区域与其他几个功能专门的区域集高度连接，并且可能对感觉运动整合很重要。本研究尝试使用数据驱动、多模式、全多层脑磁图 (MEG) 基于连接的管道来表征典型表达语言功能中涉及的连接器集线器。