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Trends in Cognitive Sciences· Laura Gwilliams·· 24 天前AI 评分62

综述:语音理解的神经编码——持续性、并行性与时间标记

Time after time: neural codes of speech comprehension

AI 导读

Laura Gwilliams 在《Trends in Cognitive Sciences》发表综述,提出人脑将转瞬即逝的语音声学信号转化为具有持续性、并行性和时间标记的神经表征。

摘要

The acoustic signal of speech is fleeting and unfolds linearly; yet listeners must derive temporally extended and hierarchically organized linguistic structures to comprehend it. This article reviews evidence that the human brain transforms the transient auditory signal into neural representations that are persistent, parallel, and time-stamped. First, neural persistence allows information to remain available after it has disappeared from the acoustic input. Second, parallel encoding of recent inputs across multiple levels of language structure enables composition and interactions across the speech hierarchy. Third, dynamic neural representations encode both content and elapsed time, providing a flexible mechanism for preserving sequence order. Together, these representational properties reveal how the human brain transforms a continuously disappearing signal into temporally extended linguistic structures.

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来源:Trends in Cognitive Sciences · cell.com