An oscillating computational model can track pseudo-rhythmic speech by using linguistic predictions
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 o...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
eLife Sciences Publications Ltd
2021-08-01
|
Series: | eLife |
Subjects: | |
Online Access: | https://elifesciences.org/articles/68066 |
_version_ | 1797997523628982272 |
---|---|
author | Sanne ten Oever Andrea E Martin |
author_facet | Sanne ten Oever Andrea E Martin |
author_sort | Sanne ten Oever |
collection | DOAJ |
description | 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. |
first_indexed | 2024-04-11T10:34:10Z |
format | Article |
id | doaj.art-f95939fc30514fa69c2f0a6990d6cbc0 |
institution | Directory Open Access Journal |
issn | 2050-084X |
language | English |
last_indexed | 2024-04-11T10:34:10Z |
publishDate | 2021-08-01 |
publisher | eLife Sciences Publications Ltd |
record_format | Article |
series | eLife |
spelling | doaj.art-f95939fc30514fa69c2f0a6990d6cbc02022-12-22T04:29:21ZengeLife Sciences Publications LtdeLife2050-084X2021-08-011010.7554/eLife.68066An oscillating computational model can track pseudo-rhythmic speech by using linguistic predictionsSanne ten Oever0https://orcid.org/0000-0001-7547-5842Andrea E Martin1https://orcid.org/0000-0002-3395-7234Language and Computation in Neural Systems group, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands; Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, Netherlands; Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, NetherlandsLanguage and Computation in Neural Systems group, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands; Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, NetherlandsNeuronal 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.https://elifesciences.org/articles/68066speechoscillationslanguagetemporal processingprediction |
spellingShingle | Sanne ten Oever Andrea E Martin An oscillating computational model can track pseudo-rhythmic speech by using linguistic predictions eLife speech oscillations language temporal processing prediction |
title | An oscillating computational model can track pseudo-rhythmic speech by using linguistic predictions |
title_full | An oscillating computational model can track pseudo-rhythmic speech by using linguistic predictions |
title_fullStr | An oscillating computational model can track pseudo-rhythmic speech by using linguistic predictions |
title_full_unstemmed | An oscillating computational model can track pseudo-rhythmic speech by using linguistic predictions |
title_short | An oscillating computational model can track pseudo-rhythmic speech by using linguistic predictions |
title_sort | oscillating computational model can track pseudo rhythmic speech by using linguistic predictions |
topic | speech oscillations language temporal processing prediction |
url | https://elifesciences.org/articles/68066 |
work_keys_str_mv | AT sannetenoever anoscillatingcomputationalmodelcantrackpseudorhythmicspeechbyusinglinguisticpredictions AT andreaemartin anoscillatingcomputationalmodelcantrackpseudorhythmicspeechbyusinglinguisticpredictions AT sannetenoever oscillatingcomputationalmodelcantrackpseudorhythmicspeechbyusinglinguisticpredictions AT andreaemartin oscillatingcomputationalmodelcantrackpseudorhythmicspeechbyusinglinguisticpredictions |