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句子生成过程中语言信息的一种与量级无关的神经编码。

A magnitude-independent neural code for linguistic information during sentence production.

作者信息

Morgan Adam M, Devinsky Orrin, Doyle Werner K, Dugan Patricia, Friedman Daniel, Flinker Adeen

机构信息

Neurology Department, NYU Grossman School of Medicine, 550 1st Ave, New York, 10016, NY, USA.

Neurosurgery Department, NYU Grossman School of Medicine, 550 1st Ave, New York, 10016, NY, USA.

出版信息

bioRxiv. 2025 Apr 3:2024.06.20.599931. doi: 10.1101/2024.06.20.599931.

DOI:10.1101/2024.06.20.599931
PMID:38948730
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11212956/
Abstract

Humans are the only species with the ability to convey an unbounded number of novel thoughts by combining words into sentences. This process is guided by complex syntactic and semantic processes. Despite their centrality to human cognition, the neural mechanisms underlying these systems remain obscured by inherent limitations of non-invasive brain measures and a near total focus on comprehension paradigms. Here, we address these limitations with high-resolution neurosurgical recordings (electrocorticography) and a controlled sentence production experiment. We uncover distinct cortical networks encoding word-level, semantic, and syntactic information. These networks are broadly distributed across traditional language areas, but with focal sensitivity to syntactic structure in middle and inferior frontal gyri. In contrast to previous findings from comprehension studies, we find that these networks are largely non-overlapping, each specialized for just one of the three linguistic constructs we investigate. Most strikingly, our data reveal an unexpected property of syntax and semantics: it is encoded independent of neural activity levels. We hypothesize that this "magnitude-independent" coding scheme likely reflects the distributed nature of these higher-order cognitive constructs.

摘要

人类是唯一有能力通过将词语组合成句子来表达无数新颖思想的物种。这一过程由复杂的句法和语义过程引导。尽管这些系统对人类认知至关重要,但这些系统背后的神经机制仍因非侵入性脑测量的固有局限性以及几乎完全专注于理解范式而变得模糊不清。在此,我们通过高分辨率神经外科记录(皮层脑电图)和一个可控的句子生成实验来解决这些局限性。我们发现了编码单词层面、语义和句法信息的不同皮层网络。这些网络广泛分布于传统语言区域,但对额中回和额下回的句法结构具有局部敏感性。与先前理解研究的结果不同,我们发现这些网络在很大程度上是不重叠的,每个网络仅专门负责我们所研究的三种语言结构中的一种。最引人注目的是,我们的数据揭示了句法和语义的一个意想不到的特性:它是独立于神经活动水平进行编码的。我们推测这种“与量级无关”的编码方案可能反映了这些高阶认知结构的分布式性质。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/11974370/79584059ab52/nihpp-2024.06.20.599931v4-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/11974370/b42fd0a88bb0/nihpp-2024.06.20.599931v4-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/11974370/2faa1b0d14b1/nihpp-2024.06.20.599931v4-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/11974370/dfd9821c01a9/nihpp-2024.06.20.599931v4-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/11974370/79584059ab52/nihpp-2024.06.20.599931v4-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/11974370/b42fd0a88bb0/nihpp-2024.06.20.599931v4-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/11974370/2faa1b0d14b1/nihpp-2024.06.20.599931v4-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/11974370/dfd9821c01a9/nihpp-2024.06.20.599931v4-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efd/11974370/79584059ab52/nihpp-2024.06.20.599931v4-f0004.jpg

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本文引用的文献

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Distributed Sensitivity to Syntax and Semantics throughout the Language Network.语言网络中对句法和语义的分布式敏感性。
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Diverging neural dynamics for syntactic structure building in naturalistic speaking and listening.自然语言听说中句法结构构建的神经动力学差异。
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Single-neuronal elements of speech production in humans.人类言语产生中单神经元的成分。
Nature. 2024 Feb;626(7999):603-610. doi: 10.1038/s41586-023-06982-w. Epub 2024 Jan 31.
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Semantic Representations during Language Comprehension Are Affected by Context.语言理解过程中的语义表示受上下文影响。
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