Phase resetting in human auditory cortex to visual speech
Bibliographic record
Abstract
ABSTRACT Natural conversation is multisensory: when we can see the speaker’s face, visual speech cues influence our perception of what is being said. The neuronal basis of this phenomenon remains unclear, though there is indication that phase modulation of neuronal oscillations—ongoing excitability fluctuations of neuronal populations in the brain—provides a mechanistic contribution. Investigating this question using naturalistic audiovisual speech with intracranial recordings in humans, we show that neuronal populations in auditory cortex track the temporal dynamics of unisensory visual speech using the phase of their slow oscillations and phase-related modulations in high-frequency activity. Auditory cortex thus builds a representation of the speech stream’s envelope based on visual speech alone, at least in part by resetting the phase of its ongoing oscillations. Phase reset could amplify the representation of the speech stream and organize the information contained in neuronal activity patterns. SIGNIFICANCE STATEMENT Watching the speaker can facilitate our understanding of what is being said. The mechanisms responsible for this influence of visual cues on the processing of speech remain incompletely understood. We studied those mechanisms by recording the human brain’s electrical activity through electrodes implanted surgically inside the skull. We found that some regions of cerebral cortex that process auditory speech also respond to visual speech even when it is shown as a silent movie without a soundtrack. This response can occur through a reset of the phase of ongoing oscillations, which helps augment the response of auditory cortex to audiovisual speech. Our results contribute to discover the mechanisms by which the brain merges auditory and visual speech into a unitary perception.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".