Combining predictive coding and neural oscillations enables online syllable recognition in natural speech
The authors present a model to parse and recognise syllables on-line in natural speech sentences that combine predictive coding and neural oscillations. They use simulations from different versions of the model to establish the importance of both theta-gamma coupling and the reset of accumulated evi...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2020
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/bb4efecc87414a518c7fadf28ade739e |
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| Sumario: | The authors present a model to parse and recognise syllables on-line in natural speech sentences that combine predictive coding and neural oscillations. They use simulations from different versions of the model to establish the importance of both theta-gamma coupling and the reset of accumulated evidence in continuous speech processing. |
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