Fuertinger Stefan, Horwitz Barry, Simonyan Kristina
Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.
Brain Imaging and Modeling Section, National Institute on Deafness and Other Communication Disorders, National Institutes of Health, Bethesda, Maryland, United States of America.
PLoS Biol. 2015 Jul 23;13(7):e1002209. doi: 10.1371/journal.pbio.1002209. eCollection 2015 Jul.
In the past few years, several studies have been directed to understanding the complexity of functional interactions between different brain regions during various human behaviors. Among these, neuroimaging research installed the notion that speech and language require an orchestration of brain regions for comprehension, planning, and integration of a heard sound with a spoken word. However, these studies have been largely limited to mapping the neural correlates of separate speech elements and examining distinct cortical or subcortical circuits involved in different aspects of speech control. As a result, the complexity of the brain network machinery controlling speech and language remained largely unknown. Using graph theoretical analysis of functional MRI (fMRI) data in healthy subjects, we quantified the large-scale speech network topology by constructing functional brain networks of increasing hierarchy from the resting state to motor output of meaningless syllables to complex production of real-life speech as well as compared to non-speech-related sequential finger tapping and pure tone discrimination networks. We identified a segregated network of highly connected local neural communities (hubs) in the primary sensorimotor and parietal regions, which formed a commonly shared core hub network across the examined conditions, with the left area 4p playing an important role in speech network organization. These sensorimotor core hubs exhibited features of flexible hubs based on their participation in several functional domains across different networks and ability to adaptively switch long-range functional connectivity depending on task content, resulting in a distinct community structure of each examined network. Specifically, compared to other tasks, speech production was characterized by the formation of six distinct neural communities with specialized recruitment of the prefrontal cortex, insula, putamen, and thalamus, which collectively forged the formation of the functional speech connectome. In addition, the observed capacity of the primary sensorimotor cortex to exhibit operational heterogeneity challenged the established concept of unimodality of this region.
在过去几年中,已有多项研究致力于理解人类在各种行为过程中不同脑区之间功能相互作用的复杂性。其中,神经影像学研究提出了这样一种观念,即言语和语言需要多个脑区协同运作,以实现对听到的声音进行理解、规划,并将其与说出的单词进行整合。然而,这些研究在很大程度上仅限于绘制单独言语元素的神经关联,并检查参与言语控制不同方面的不同皮质或皮质下回路。因此,控制言语和语言的脑网络机制的复杂性在很大程度上仍然未知。我们通过对健康受试者的功能磁共振成像(fMRI)数据进行图论分析,构建了从静息状态到无意义音节的运动输出,再到现实生活中复杂言语产生过程中层次不断增加的功能性脑网络,以此来量化大规模言语网络拓扑结构,并与非言语相关的顺序手指敲击和纯音辨别网络进行比较。我们在初级感觉运动和顶叶区域识别出一个由高度连接的局部神经群落(中枢)组成的分离网络,该网络在所有检查条件下形成了一个共同共享的核心中枢网络,其中左侧4p区在言语网络组织中发挥着重要作用。这些感觉运动核心中枢基于它们参与不同网络中的多个功能域以及根据任务内容自适应切换远程功能连接的能力,表现出灵活中枢的特征,从而导致每个检查网络具有独特的群落结构。具体而言,与其他任务相比,言语产生的特征是形成了六个不同的神经群落,前额叶皮质、岛叶、壳核和丘脑有专门的募集,它们共同促成了功能性言语连接组的形成。此外,初级感觉运动皮质表现出的操作异质性挑战了该区域单模态的既定概念。