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Nature Communications· 2026Q1

Top-down semantic predictions align phonetic neuronal dynamics in human superior temporal gyrus

Pavo Orepić, Wilson Truccolo, Eric Halgren, Sydney S. Cash et al.

Short summary

Neuronal population dynamics in the human superior temporal gyrus concurrently encode phonetic and semantic speech features, with top-down semantic predictions influencing phonetic representations.

AI-generated from the title and abstract; the full text is not read.

Key points

  • Distinct neural manifolds for semantic and phonetic speech features were identified in the human superior temporal gyrus.
  • These semantic and phonetic representations were encoded concurrently.
  • Power increases in beta and low-gamma local field potentials reflected concurrent phonetic and semantic encoding.
  • The study provides the first demonstration of mechanisms for hierarchical speech transformations specific to neuronal population dynamics.

AI-generated from the title and abstract; the full text is not read.

Abstract

Traditional models of speech perception posit that neural activity encodes speech through a hierarchy of cognitive processes, from low-level representations of acoustic and phonetic features to high-level semantic encoding. Yet it remains unknown how neural representations are transformed across levels of the speech hierarchy. Here, we analyzed unique microelectrode array recordings of neuronal spiking activity from the human left anterior superior temporal gyrus, a brain region at the interface between phonetic and semantic speech processing, during a semantic categorization task and natural speech perception. We identified distinct neural manifolds for semantic and phonetic features, with a functional separation of the corresponding low-dimensional trajectories. Moreover, phonetic and semantic representations were encoded concurrently and reflected in power increases in the beta and low-gamma local field potentials, suggesting top-down predictive and bottom-up cumulative processes. Our results are the first to demonstrate mechanisms for hierarchical speech transformations that are specific to neuronal population dynamics.

The authors' abstract, as published at the source. Nature Communications, 2026 · DOI ↗

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Field: Cognitive Neuroscience

Cognitive NeuroscienceNeuroscience