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Quantitative Biology > Neurons and Cognition

arXiv:2502.07429 (q-bio)
[Submitted on 11 Feb 2025 (v1) , last revised 18 Feb 2025 (this version, v2)]

Title: From Thought to Action: How a Hierarchy of Neural Dynamics Supports Language Production

Title: 从思想到行动:神经动力学层次如何支持语言产生

Authors:Mingfang Zhang, Jarod Lévy, Stéphane d'Ascoli, Jérémy Rapin, F.-Xavier Alario, Pierre Bourdillon, Svetlana Pinet, Jean-Rémi King
Abstract: Humans effortlessly communicate their thoughts through intricate sequences of motor actions. Yet, the neural processes that coordinate language production remain largely unknown, in part because speech artifacts limit the use of neuroimaging. To elucidate the unfolding of language production in the brain, we investigate with magnetoencephalography (MEG) and electroencephalography (EEG) the neurophysiological activity of 35 skilled typists, while they typed sentences on a keyboard. This approach confirms the hierarchical predictions of linguistic theories: the neural activity preceding the production of each word is marked by the sequential rise and fall of context-, word-, syllable-, and letter-level representations. Remarkably, each of these neural representations is maintained over long time periods within each level of the language hierarchy. This phenomenon results in a superposition of successive representations that is supported by a hierarchy of dynamic neural codes. Overall, these findings provide a precise computational breakdown of the neural dynamics that coordinate the production of language in the human brain.
Abstract: 人类能够轻松地通过复杂的运动动作序列来传达他们的想法。 然而,协调语言产生的神经过程在很大程度上仍然未知,部分原因是语音伪影限制了神经成像的使用。 为了阐明大脑中语言产生的展开过程,我们利用磁脑图(MEG)和脑电图(EEG)研究了35名熟练打字者在键盘上输入句子时的神经生理活动。 这种方法验证了语言理论的层次预测:每个词语产生之前的神经活动表现出上下文、词语、音节和字母层级表征的顺序上升和下降。 值得注意的是,这些神经表征在语言层次的每个层级内都能维持较长时间。 这种现象导致了连续表征的叠加,这由动态神经代码的层次结构所支持。 总体而言,这些发现提供了对协调人类大脑语言产生的神经动力学的精确计算分解。
Subjects: Neurons and Cognition (q-bio.NC)
Cite as: arXiv:2502.07429 [q-bio.NC]
  (or arXiv:2502.07429v2 [q-bio.NC] for this version)
  https://doi.org/10.48550/arXiv.2502.07429
arXiv-issued DOI via DataCite

Submission history

From: Mingfang Zhang [view email]
[v1] Tue, 11 Feb 2025 10:17:38 UTC (13,838 KB)
[v2] Tue, 18 Feb 2025 14:56:47 UTC (13,838 KB)
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