ArticleeLife2021
An oscillating computational model can track pseudo-rhythmic speech by using linguistic predictions.
Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Effects of speech periodicity and speech rate on auditory-motor coupling during speech comprehension.Communications biology · 2026Article
- Computational modeling of rhythmic expectations: Perspectives, pitfalls, and prospects.PLoS computational biology · 2025Review
- Left Perisylvian Rhythms Encode Prosody and Syntax during Delayed Sentence Repetition.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Supplementary motor area in speech initiation: A large-scale intracranial EEG evaluation of stereotyped word articulation.iScience · 2025Article
- Neural encoding of melodic expectations in music across EEG frequency bands.The European journal of neuroscience · 2024Article
- Reclaiming AI as a Theoretical Tool for Cognitive Science.Computational brain & behavior · 2024Article
- The structure and statistics of language jointly shape cross-frequency neural dynamics during spoken language comprehension.Nature communications · 2024Article
- Early language experience modulates the tradeoff between acoustic-temporal and lexico-semantic cortical tracking of speech.iScience · 2024Article
- Speech Prosody Serves Temporal Prediction of Language via Contextual Entrainment.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Phase-dependent word perception emerges from region-specific sensitivity to the statistics of language.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Alpha and Beta Oscillations Differentially Support Word Production in a Rule-Switching Task.eNeuro · 2024Article
- Specificity of Motor Contributions to Auditory Statistical Learning.Journal of cognition · 2024Article
- Lexical Surprisal Shapes the Time Course of Syntactic Structure Building.Neurobiology of language (Cambridge, Mass.) · 2024Article
- Rhythms in Speech.Advances in experimental medicine and biology · 2024Review
- What is a Rhythm for the Brain? The Impact of Contextual Temporal Variability on Auditory Perception.Journal of cognition · 2024Article
- Adaptive oscillators support Bayesian prediction in temporal processing.PLoS computational biology · 2023Article
- A tradeoff between acoustic and linguistic feature encoding in spoken language comprehension.eLife · 2023Article
- Naturalistic Spoken Language Comprehension Is Supported by Alpha and Beta Oscillations.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Dynamics of Functional Networks for Syllable and Word-Level Processing.Neurobiology of language (Cambridge, Mass.) · 2023Article
- Tracking human skill learning with a hierarchical Bayesian sequence model.PLoS computational biology · 2022Article
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2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Neuronal oscillations putatively track speech in order to optimize sensory processing. However, it is unclear how isochronous brain oscillations can track pseudo-rhythmic speech input. Here we propose that oscillations can track pseudo-rhythmic speech when considering that speech time is dependent on content-based predictions flowing from internal language models. We show that temporal dynamics of speech are dependent on the predictability of words in a sentence. A computational model including oscillations, feedback, and inhibition is able to track pseudo-rhythmic speech input. As the model processes, it generates temporal phase codes, which are a candidate mechanism for carrying information forward in time. The model is optimally sensitive to the natural temporal speech dynamics and can explain empirical data on temporal speech illusions. Our results suggest that speech tracking does not have to rely only on the acoustics but could also exploit ongoing interactions between oscillations and constraints flowing from internal language models.
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