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一项使用脑皮层电图在非实验性、自然公开言语产生条件下对词汇复杂性的研究。

A Study of Word Complexity Under Conditions of Non-experimental, Natural Overt Speech Production Using ECoG.

作者信息

Glanz Olga, Hader Marina, Schulze-Bonhage Andreas, Auer Peter, Ball Tonio

机构信息

GRK 1624 "Frequency Effects in Language," University of Freiburg, Freiburg, Germany.

Department of German Linguistics, University of Freiburg, Freiburg, Germany.

出版信息

Front Hum Neurosci. 2022 Feb 4;15:711886. doi: 10.3389/fnhum.2021.711886. eCollection 2021.

DOI:10.3389/fnhum.2021.711886
PMID:35185491
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8854223/
Abstract

The linguistic complexity of words has largely been studied on the behavioral level and in experimental settings. Only little is known about the neural processes underlying it in uninstructed, spontaneous conversations. We built up a multimodal neurolinguistic corpus composed of synchronized audio, video, and electrocorticographic (ECoG) recordings from the fronto-temporo-parietal cortex to address this phenomenon based on uninstructed, spontaneous speech production. We performed extensive linguistic annotations of the language material and calculated word complexity using several numeric parameters. We orthogonalized the parameters with the help of a linear regression model. Then, we correlated the spectral components of neural activity with the individual linguistic parameters and with the residuals of the linear regression model, and compared the results. The proportional relation between the number of consonants and vowels, which was the most informative parameter with regard to the neural representation of word complexity, showed effects in two areas: the frontal one was at the junction of the premotor cortex, the prefrontal cortex, and Brodmann area 44. The postcentral one lay directly above the lateral sulcus and comprised the ventral central sulcus, the parietal operculum and the adjacent inferior parietal cortex. Beyond the physiological findings summarized here, our methods may be useful for those interested in ways of studying neural effects related to natural language production and in surmounting the intrinsic problem of collinearity between multiple features of spontaneously spoken material.

摘要

单词的语言复杂性在很大程度上是在行为层面和实验环境中进行研究的。对于自然、自发对话中其背后的神经过程,人们了解甚少。我们构建了一个多模态神经语言学语料库,该语料库由来自额颞顶叶皮层的同步音频、视频和皮层脑电图(ECoG)记录组成,以基于自然、自发的言语产生来研究这一现象。我们对语言材料进行了广泛的语言标注,并使用几个数值参数计算单词复杂性。我们借助线性回归模型对这些参数进行了正交化处理。然后,我们将神经活动的频谱成分与各个语言参数以及线性回归模型的残差进行关联,并比较结果。辅音和元音数量之间的比例关系,这是关于单词复杂性神经表征最具信息量的参数,在两个区域显示出效应:额叶区域位于运动前皮层、前额叶皮层和布罗德曼区44的交界处。中央后区域直接位于外侧沟上方,包括腹侧中央沟、顶叶岛盖和相邻的下顶叶皮层。除了这里总结的生理学发现外,我们的方法可能对那些对研究与自然语言产生相关的神经效应以及克服自发口语材料多个特征之间共线性这一内在问题的方法感兴趣的人有用。

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