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自然语言理解过程中工作记忆需求对语言选择皮层的强大影响。

Robust Effects of Working Memory Demand during Naturalistic Language Comprehension in Language-Selective Cortex.

作者信息

Shain Cory, Blank Idan A, Fedorenko Evelina, Gibson Edward, Schuler William

机构信息

Massachusetts Institute of Technology, Cambridge, Massachusetts 02478

University of California, Los Angeles, Los Angeles, California 90095.

出版信息

J Neurosci. 2022 Sep 28;42(39):7412-7430. doi: 10.1523/JNEUROSCI.1894-21.2022.

Abstract

To understand language, we must infer structured meanings from real-time auditory or visual signals. Researchers have long focused on word-by-word structure building in working memory as a mechanism that might enable this feat. However, some have argued that language processing does not typically involve rich word-by-word structure building, and/or that apparent working memory effects are underlyingly driven by (how predictable a word is in context). Consistent with this alternative, some recent behavioral studies of naturalistic language processing that control for surprisal have not shown clear working memory effects. In this fMRI study, we investigate a range of theory-driven predictors of word-by-word working memory demand during naturalistic language comprehension in humans of both sexes under rigorous surprisal controls. In addition, we address a related debate about whether the working memory mechanisms involved in language comprehension are language specialized or domain general. To do so, in each participant, we functionally localize (1) the language-selective network and (2) the "multiple-demand" network, which supports working memory across domains. Results show robust surprisal-independent effects of memory demand in the language network and no effect of memory demand in the multiple-demand network. Our findings thus support the view that language comprehension involves computationally demanding word-by-word structure building operations in working memory, in addition to any prediction-related mechanisms. Further, these memory operations appear to be primarily conducted by the same neural resources that store linguistic knowledge, with no evidence of involvement of brain regions known to support working memory across domains. This study uses fMRI to investigate signatures of working memory (WM) demand during naturalistic story listening, using a broad range of theoretically motivated estimates of WM demand. Results support a strong effect of WM demand in the brain that is distinct from effects of word predictability. Further, these WM demands register primarily in language-selective regions, rather than in "multiple-demand" regions that have previously been associated with WM in nonlinguistic domains. Our findings support a core role for WM in incremental language processing, using WM resources that are specialized for language.

摘要

为了理解语言,我们必须从实时听觉或视觉信号中推断出结构化的含义。长期以来,研究人员一直将工作记忆中逐词构建结构视为一种可能实现这一壮举的机制。然而,一些人认为语言处理通常并不涉及丰富的逐词结构构建,和/或认为明显的工作记忆效应实际上是由(一个词在语境中的可预测程度)驱动的。与此观点一致的是,最近一些控制了意外性的自然语言处理行为研究并未显示出明显的工作记忆效应。在这项功能磁共振成像(fMRI)研究中,我们在严格的意外性控制下,调查了一系列理论驱动的预测因子,这些因子与男女在自然语言理解过程中逐词工作记忆需求有关。此外,我们还探讨了一个相关的争论,即语言理解中涉及的工作记忆机制是语言特有的还是领域通用的。为此,在每个参与者身上,我们通过功能定位(1)语言选择网络和(2)“多需求”网络,后者支持跨领域的工作记忆。结果表明,语言网络中存在与意外性无关的强大记忆需求效应,而多需求网络中不存在记忆需求效应。因此,我们的研究结果支持这样一种观点,即除了任何与预测相关的机制外,语言理解还涉及工作记忆中需要大量计算的逐词结构构建操作。此外,这些记忆操作似乎主要由存储语言知识的相同神经资源进行,没有证据表明支持跨领域工作记忆的脑区参与其中。本研究使用功能磁共振成像来调查自然故事聆听过程中工作记忆(WM)需求的特征,使用了一系列基于理论的广泛WM需求估计。结果支持WM需求在大脑中产生的强大效应,这与词的可预测性效应不同。此外,这些WM需求主要记录在语言选择区域,而不是先前在非语言领域与WM相关的“多需求”区域。我们的研究结果支持WM在增量语言处理中发挥核心作用,使用专门用于语言的WM资源。

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