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言语加工过程中预测性脑机制的时空动态:一项 MEG 研究。

Spatiotemporal dynamics of predictive brain mechanisms during speech processing: an MEG study.

机构信息

Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China; McGovern Institute for Brain Research, Peking University, Beijing, China.

Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China; McGovern Institute for Brain Research, Peking University, Beijing, China.

出版信息

Brain Lang. 2020 Apr;203:104755. doi: 10.1016/j.bandl.2020.104755. Epub 2020 Jan 30.

Abstract

Rapid and efficient speech processing benefits from the prediction derived from prior expectations based on the identification of individual words. It is known that speech processing is carried out within a distributed frontotemporal network. However, the spatiotemporal causal dynamics of predictive brain mechanisms in sound-to-meaning mapping within this network remain unclear. Using magnetoencephalography, we adopted a semantic anomaly paradigm which consists of expected, unexpected and time-reversed Mandarin Chinese speech, and localized the effects of violated expectation in frontotemporal brain regions, the sensorimotor cortex and the supramarginal gyrus from 250 ms relative to the target words. By further investigating the causal cortical dynamics, we provided the description of the causal dynamic network within the framework of the dual stream model, and highlighted the importance of the connections within the ventral pathway, the top-down modulation from the left inferior frontal gyrus and the cross-stream integration during the speech processing of violated expectation.

摘要

快速而有效的言语处理得益于基于识别单个单词的先验期望的预测。已知言语处理是在一个额颞分布式网络中进行的。然而,在这个网络中,从声音到意义映射的预测性大脑机制的时空因果动力学仍然不清楚。使用脑磁图,我们采用了一种语义异常范式,该范式由预期的、意外的和时间反转的汉语语音组成,并从目标词开始 250 毫秒后定位了额颞脑区、感觉运动皮层和缘上回中违反预期的影响。通过进一步研究因果皮质动力学,我们在双流模型的框架内描述了因果动态网络,并强调了在违反预期的言语处理过程中,腹侧通路内的连接、来自左额下回的自上而下的调制以及跨流整合的重要性。

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