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

Abstract Speech processing involves a hierarchy of cognitive layers from low-level phonetic to high-level semantic representations. However, interactions are not only feed-forward; feedback mechanisms are crucial for real-time, accurate speech recognition. Yet how distant levels interface during speech processing remains unclear. Here, we analyzed intracortical recordings from 624 neurons across three human participants implanted with microelectrode arrays in the anterior superior temporal gyrus during an auditory semantic categorization task and natural speech perception. We identified distinct neural subspaces, or manifolds, for lexico-semantic and phonetic features, with a functional separation of the corresponding low-dimensional dynamics. We contrasted a bottom-up cumulative and a top-down semantic hypothesis on phonetic-semantic temporal alignment, and found phonetic alignment to word-level semantic representations, signaling top-down prediction. These effects were consistent across participants at the spiking level, and remained undetected in adjacent ECoG recordings. These findings demonstrate the reorganization of neuronal population dynamics supporting phonetic representations during semantic prediction.

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Publication Details

Journal
Nature Communications
Published
2026-10-03
DOI
https://doi.org/10.1038/s41467-026-77942-x
Primary Topic
Neural dynamics and brain function
Type
article
Field-Weighted Citation Impact
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article

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

Timothée Proix, Pavo Orepić, Sydney S. Cash, Anne‐Lise Giraud et al.
Nature Communications
Neural dynamics and brain function
article

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

Timothée Proix, Pavo Orepić, Sydney S. Cash, Anne‐Lise Giraud, Wilson Truccolo, Eric Halgren
article en

Abstract

Abstract Speech processing involves a hierarchy of cognitive layers from low-level phonetic to high-level semantic representations. However, interactions are not only feed-forward; feedback mechanisms are crucial for real-time, accurate speech recognition. Yet how distant levels interface during speech processing remains unclear. Here, we analyzed intracortical recordings from 624 neurons across three human participants implanted with microelectrode arrays in the anterior superior temporal gyrus during an auditory semantic categorization task and natural speech perception. We identified distinct neural subspaces, or manifolds, for lexico-semantic and phonetic features, with a functional separation of the corresponding low-dimensional dynamics. We contrasted a bottom-up cumulative and a top-down semantic hypothesis on phonetic-semantic temporal alignment, and found phonetic alignment to word-level semantic representations, signaling top-down prediction. These effects were consistent across participants at the spiking level, and remained undetected in adjacent ECoG recordings. These findings demonstrate the reorganization of neuronal population dynamics supporting phonetic representations during semantic prediction.

Nature Communications
University of Geneva (CH), Harvard University (US), Institut Pasteur (FR), University of Zurich (CH), Université Paris Cité (FR), Brown University (US), ETH Zurich (CH), University of California San Diego (US), Massachusetts General Hospital (US), Institute of Neuroinformatics (CH)
Openalex Percentile: Top 10%
Neural dynamics and brain function
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