Abstract

Communication through spoken language is a central human capacity, involving a wide range of complex computations that incrementally interpret each word into meaningful sentences. However, surprisingly little is known about the spatiotemporal properties of the complex neurobiological systems that support these dynamic predictive and integrative computations. Here, we focus on prediction, a core incremental processing operation guiding the interpretation of each upcoming word with respect to its preceding context. To investigate the neurobiological basis of how semantic constraints change and evolve as each word in a sentence accumulates over time, in a spoken sentence comprehension study, we analyzed the multivariate patterns of neural activity recorded by source-localized electro/magnetoencephalography (EMEG), using computational models capturing semantic constraints derived from the prior context on each upcoming word. Our results provide insights into predictive operations subserved by different regions within a bi-hemispheric system, which over time generate, refine, and evaluate constraints on each word as it is heard.

中文翻译：

---

解码增量语义解释的实时神经生物学特性。

摘要

通过口语交流是人类的一项核心能力，涉及范围广泛的复杂计算，这些计算逐步将每个单词解释为有意义的句子。然而，令人惊讶的是，人们对支持这些动态预测和综合计算的复杂神经生物学系统的时空特性知之甚少。在这里，我们专注于预测，这是一个核心的增量处理操作，指导每个即将出现的单词相对于其先前上下文的解释。为了研究语义约束如何随着句子中的每个词随着时间的推移而变化和演变的神经生物学基础，在口语理解研究中，我们分析了源定位电/脑磁图 (EMEG) 记录的神经活动的多元模式，使用计算模型捕获从每个即将出现的单词的先验上下文得出的语义约束。我们的结果提供了对双半球系统内不同区域所支持的预测操作的见解，随着时间的推移，该系统会在听到每个单词时生成、改进和评估对每个单词的约束。