Robust Effects of Working Memory Demand during Naturalistic Language Comprehension in Language-Selective Cortex
Robust Effects of Working Memory Demand during Naturalistic Language Comprehension in Language-Selective Cortex
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DOI：
10.1101/2021.09.18.460917
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发表时间：
2021-01
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影响因子：
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通讯作者：
Cory Shain;I. Blank;Evelina Fedorenko;E. Gibson;William Schuler
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作者：
Cory Shain;I. Blank;Evelina Fedorenko;E. Gibson;William Schuler
为了理解语言，我们必须从实时的听觉或视觉信号中推断出结构化的含义。长期以来，研究人员一直关注工作记忆中逐字结构的构建，认为这可能是实现这一壮举的一种机制。然而，一些人认为语言处理通常不涉及丰富的逐字结构构建，并且/或者明显的工作记忆效应是由惊喜（单词在上下文中的可预测性）驱动的。与这一观点一致的是，最近一些关于控制惊讶的自然语言处理的行为研究并没有显示出明确的工作记忆效应。在这项功能磁共振成像研究中，我们研究了一系列理论驱动的预测因素，在严格的惊喜控制下，男女在自然语言理解过程中逐字工作记忆需求。此外，我们还讨论了与语言理解相关的工作记忆机制是语言专门化的还是领域通用的。为此，我们对每个参与者进行功能定位(1)语言选择网络和(2)支持跨领域工作记忆的“多需求”网络。结果表明，语言网络对记忆需求具有显著的非惊讶性影响，而多需求网络对记忆需求没有影响。因此，我们的研究结果支持了这样一种观点，即除了任何与预测相关的机制外，语言理解还包括在工作记忆中逐字计算要求的结构构建操作。此外，这些记忆操作似乎主要是由存储语言知识的相同神经资源进行的，没有证据表明支持跨领域工作记忆的大脑区域参与其中。本研究使用功能磁共振成像（fMRI）研究自然故事听过程中工作记忆（WM）需求的特征，采用广泛的理论动机估计WM需求。研究结果表明，大脑对词汇的需求有很强的影响，这与词汇可预见性的影响不同。此外，这些WM需求主要在语言选择区域注册，而不是在以前与非语言领域的WM相关的“多需求”区域注册。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。
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 surprisal (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. SIGNIFICANCE STATEMENT 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.