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A systems perspective on the effective connectivity of overt speech production

机译:从系统角度看公开语音制作的有效连通性

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摘要

The aim of this study was to provide a computational system model of effective connectivity in the human brain underlying overt speech production. Meta-analysis of neuroimaging studies and functional magnetic resonance imaging data acquired during a verbal fluency task revealed a core network consisting of Brodmann's area (BA) 44 in Broca's region, anterior insula, basal ganglia, cerebellum, premotor cortex (PMC, BA 6) and primary motor cortex (M1, areas 4a/4p). Dynamic causal modelling (DCM) indicated the highest evidence for a system architecture featuring the insula in a serial position between BA 44 and two parallel nodes (cerebellum/basal ganglia), from which information converges onto the PMC and finally M1. Parameter inference revealed that effective connectivity from the insular relay into the cerebellum/basal ganglia is primarily task driven (preparation) while the output into the cortical motor system strongly depends on the actual word production rate (execution). DCM hence allowed not only a quantitative characterization of the human speech production network, but also the distinction of a preparatory and an executive subsystem within it. The proposed model of physiological integration during speech production may now serve as a reference for investigations into the neurobiology of pathological states such as dysarthria and apraxia of speech.
机译:这项研究的目的是提供一种基于公开语音产生的人脑中有效连接的计算系统模型。在口语流利任务期间对神经影像学研究和功能性磁共振成像数据进行的荟萃分析显示,核心网络由Broca区域的Brodmann区域(BA)44,前岛岛,基底神经节,小脑,运动前皮质(PMC,BA 6)组成和初级运动皮层(M1,区域4a / 4p)。动态因果建模(DCM)为系统架构提供了最高的证据,该系统的特征是绝缘体位于BA 44和两个并行节点(小脑/基底神经节)之间的串行位置,信息从这些节点汇聚到PMC上,最后汇聚到M1上。参数推断表明,从岛状中继器到小脑/基底神经节的有效连接主要是任务驱动(准备),而进入皮层运动系统的输出很大程度上取决于实际的词产生率(执行)。因此,DCM不仅可以定量描述人类语音生成网络,还可以区分其中的准备子系统和执行子系统。在语音产生过程中提出的生理整合模型现在可以作为研究病理状态(例如构音障碍和语音失用)的神经生物学的参考。

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