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Peer-reviewedCC BY 4.0Nature Communications

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

  • Pavo Orepić1
  • Wilson Truccolo2,3
  • Eric Halgren4
  • Sydney S. Cash5
  • Anne‐Lise Giraud1,6
  • Timothée Proix7
7 affiliations
  1. 1Department of Basic Neurosciences, Faculty of Medicine, University of Geneva, Geneva, Switzerland
  2. 2Carney Institute for Brain Science, Brown University, Providence, RI, USA
  3. 3Department of Neuroscience, Brown University, Providence, RI, USA
  4. 4Department of Neuroscience & Radiology, University of California San Diego, La Jolla, CA, USA
  5. 5Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
  6. 6Institut Pasteur, Université Paris Cité, Hearing Institute, Paris, France
  7. 7Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland
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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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Cite

BibTeXRIS
BibTeX
@article{orepic2026topdown,
  title = {{Top-down semantic predictions align phonetic neuronal dynamics in human superior temporal gyrus}},
  author = {Pavo Orepić and Wilson Truccolo and Eric Halgren and Sydney S. Cash and Anne‐Lise Giraud and Timothée Proix},
  journal = {Nature Communications},
  year = {2026},
  month = oct,
  doi = {10.1038/s41467-026-77942-x},
  url = {https://www.nature.com/articles/s41467-026-77942-x},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Top-down semantic predictions align phonetic neuronal dynamics in human superior temporal gyrus
AU  - Pavo Orepić
AU  - Wilson Truccolo
AU  - Eric Halgren
AU  - Sydney S. Cash
AU  - Anne‐Lise Giraud
AU  - Timothée Proix
PY  - 2026
DA  - 2026/10/03
JO  - Nature Communications
DO  - 10.1038/s41467-026-77942-x
UR  - https://www.nature.com/articles/s41467-026-77942-x
AB  - 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.
SN  - 2041-1723
ER  -