第二语言学习中大脑网络的差异取决于个体能力。

Imaging neuroscience (Cambridge, Mass.) Pub Date : 2026-09-30 eCollection Date: 2026-01-01 DOI:10.1162/IMAG.a.1379
Nicole H Skieresz, Sandy C Marca, Micah M Murray, Thomas P Reber, Nicolas Rothen
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引用次数: 0

摘要

将新单词整合到现有的语义网络中是第二语言习得的核心挑战。我们研究了基于证据的学习策略和个体表现与词汇学习的神经认知动力学之间的关系。83名精通德语或法语的成年人在14天内使用一个移动应用程序学习了48个芬兰语(L2)名词,该应用程序系统地进行了不同的检索练习、纠正反馈、多感官学习和分布式学习。在训练前后的翻译识别任务中记录EEG,以诱发语义整合指标N400。词汇正确率从学习前的0.41%提高到学习后的75.5% (dz = 3.96), N400不一致效应显著增加,F(1,75) = 99.52, p < 0.001, η²g = 0.32,反映了新词汇成功融入心理词汇。表现优异者的N400反应更大,与语义加工分化程度更高一致。此外,表现组在事件相关电位(ERP)模板图优势(即分配给给定模板图的历元时间点的比例)方面出现差异,表明处理动态和网络配置的差异。尽管有系统的学习策略,但没有一种方法能产生一致的行为或神经优势,这表明整体暴露和累积练习,而不是任何特定的策略,可能是观察到的学习收益的主要贡献者。ERP模板图分析进一步表明,学习不仅增加了神经反应,而且还改变了N400窗口内的地图优势,这是会话和一致性的函数,表明语义加工的定性重组。这些发现表明,词汇学习成功与语义整合程度的关系比与任何单一的教学策略的关系更密切。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Brain network differences in second language learning depend on individual competencies.

Integrating new words into an existing semantic network is a core challenge of second language (L2) acquisition. We investigated how evidence-based learning strategies and individual performance relate to the neurocognitive dynamics of vocabulary learning. Eighty-three adults proficient in German or French learned 48 Finnish (L2) nouns over 14 days using a mobile app that systematically varied retrieval practice, corrective feedback, multisensory learning, and distributed learning. Before and after training, EEG was recorded during a translation recognition task designed to elicit the N400, an index of semantic integration. Vocabulary accuracy increased from 0.41% pre-learning to 75.5% post-learning (dz = 3.96), and the N400 incongruity effect increased significantly, F(1, 75) = 99.52, p < .001, η²g = .32, reflecting successful integration of new L2 words into the mental lexicon. High performers showed larger N400 responses, consistent with more differentiated semantic processing. In addition, performance group differences emerged in event-related potential (ERP) template-map preponderance (i.e., the proportion of epoch time points assigned to a given template map), indicating differences in processing dynamics and network configurations. Despite systematic manipulation of learning strategies, no single approach yielded consistent behavioral or neural advantages, suggesting that overall exposure and cumulative practice, rather than any specific strategy, may have been primary contributors to the observed learning gains. ERP template-map analyses further revealed that learning not only increased neural responses but also shifted map preponderance within the N400 window as a function of Session and Congruency, indicating a qualitative reorganization of semantic processing. These findings suggest that vocabulary learning success is more closely related to the degree of semantic integration than to any single instructional strategy.

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