Time after time: neural codes of speech comprehension.

Abstract

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.