Functional connectivity between parietal and temporal lobes mediates internal forward models during speech production

IF 2.1 2区 心理学 Q1 AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY
Wenjia Zhang , Fuyin Yang , Xing Tian
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引用次数: 0

Abstract

Internal forward models hypothesize functional links between motor and sensory systems for predicting the consequences of actions. Recently, the cascaded theory proposes that somatosensory estimation in the inferior parietal lobe (IPL) can be a relay computational structure, converting motor signals into predictions of auditory consequences in a serial processing manner during speech production. The study used fMRI with functional connectivity (FC) analyses to investigate the proposed cascaded processes using three speech tasks: overt articulation (OA), silent articulation (SA) and imagined articulation (IA). The FC results showed that connectivity between aIPL and STG was increased in OA compared with SA, suggesting that the relationship between somatosensory and auditory estimations can be modulated by speech tasks. Moreover, stronger connectivity between IFGoper and pIPL, and between pIPL and STG were observed in SA and IA compared with OA. These results are consistent with a cascaded process in the internal forward models.

顶叶和颞叶之间的功能连接在言语产生过程中介导内部前向模型
内部正向模型假设运动和感觉系统之间的功能联系,以预测动作的后果。最近,级联理论提出,顶叶下叶(IPL)的体感估计可以是一种中继计算结构,在语音产生过程中以串行处理的方式将运动信号转换为听觉结果的预测。该研究使用功能连接(FC)分析的功能磁共振成像来研究所提出的使用三种语音任务的级联过程:显性发音(OA)、无声发音(SA)和想象发音(IA)。FC结果显示,与SA相比,OA中aIPL和STG之间的连接增加,这表明体感和听觉估计之间的关系可以通过语音任务来调节。此外,与OA相比,在SA和IA中观察到IFGoper和pIPL之间以及pIPL和STG之间更强的连接性。这些结果与内部正向模型中的级联过程一致。
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来源期刊
Brain and Language
Brain and Language 医学-神经科学
CiteScore
4.50
自引率
8.00%
发文量
82
审稿时长
20.5 weeks
期刊介绍: An interdisciplinary journal, Brain and Language publishes articles that elucidate the complex relationships among language, brain, and behavior. The journal covers the large variety of modern techniques in cognitive neuroscience, including functional and structural brain imaging, electrophysiology, cellular and molecular neurobiology, genetics, lesion-based approaches, and computational modeling. All articles must relate to human language and be relevant to the understanding of its neurobiological and neurocognitive bases. Published articles in the journal are expected to have significant theoretical novelty and/or practical implications, and use perspectives and methods from psychology, linguistics, and neuroscience along with brain data and brain measures.
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