Department of Otolaryngology - Head and Neck Surgery, Massachusetts Eye and Ear, 243 Charles Street, Boston, MA 02114, USA.
Department of Otolaryngology-Head and Neck Surgery, Harvard Medical School, 243 Charles Street, Boston, MA 02114, USA.
Philos Trans R Soc Lond B Biol Sci. 2021 Oct 25;376(1836):20200256. doi: 10.1098/rstb.2020.0256. Epub 2021 Sep 6.
Speech production relies on the orchestrated control of multiple brain regions. The specific, directional influences within these networks remain poorly understood. We used regression dynamic causal modelling to infer the whole-brain directed (effective) connectivity from functional magnetic resonance imaging data of 36 healthy individuals during the production of meaningful English sentences and meaningless syllables. We identified that the two dynamic connectomes have distinct architectures that are dependent on the complexity of task production. The speech was regulated by a dynamic neural network, the most influential nodes of which were centred around superior and inferior parietal areas and influenced the whole-brain network activity via long-ranging coupling with primary sensorimotor, prefrontal, temporal and insular regions. By contrast, syllable production was controlled by a more compressed, cost-efficient network structure, involving sensorimotor cortico-subcortical integration via superior parietal and cerebellar network hubs. These data demonstrate the mechanisms by which the neural network reorganizes the connectivity of its influential regions, from supporting the fundamental aspects of simple syllabic vocal motor output to multimodal information processing of speech motor output. This article is part of the theme issue 'Vocal learning in animals and humans'.
言语产生依赖于多个脑区的协调控制。这些网络中特定的、有方向的影响仍然知之甚少。我们使用回归动态因果建模，从 36 名健康个体在生成有意义的英语句子和无意义音节期间的功能磁共振成像数据中推断整个大脑的定向（有效）连接。我们发现，这两个动态连接组具有不同的结构，这取决于任务产生的复杂性。言语受到动态神经网络的调节，其中最有影响力的节点集中在顶叶和顶叶下区域周围，并通过与初级感觉运动、前额叶、颞叶和脑岛区域的长程耦合来影响整个大脑网络的活动。相比之下，音节产生受更压缩、成本效益更高的网络结构控制，涉及通过顶叶和小脑网络枢纽进行感觉运动皮质下整合。这些数据表明了神经网络如何重新组织其有影响力的区域的连接的机制，从支持简单音节发声运动输出的基本方面到言语运动输出的多模态信息处理。本文是主题为“动物和人类的发声学习”的一部分。
