ArticleIEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society2021
Low-Frequency Entrainment to Visual Motion Underlies Sign Language Comprehension.
Article in IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Predictive Processing in Sign Languages: A Systematic Review.Frontiers in psychology · 2022Pooled it
- Article
- Effect of sign language learning on temporal resolution of visual attention.Journal of vision · 2025Article
- Article
- Prediction underlying comprehension of human motion: an analysis of Deaf signer and non-signer EEG in response to visual stimuli.Frontiers in neuroscience · 2023Article
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4 authors.
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Abstract
When people listen to speech, neural activity tracks the entropy fluctuation in the acoustic envelope of the signal. This signal-based entrainment has been shown to be the basis of speech parsing and comprehension. In this electroencephalography (EEG) study, we compute sign language users' cortical tracking of changes in visual dynamics of the communicative signal in the time-direct videos of sign language, and their time-reversed counterparts, and assess the relative contribution of response frequencies between.2 and 12.4 Hz to comprehension using a machine learning approach to brain state classification. Lower frequencies of EEG response (.2-4 Hz) yield 100% classification accuracy, while information about cortical tracking of the visual envelope in higher frequencies is less informative. This suggests that signers rely on lower visual frequency data, such as envelope of visual signal, for sign language comprehension. In the context of real-time language processing, given the speed of comprehension responses, this suggests that fluent signers employ a predictive processing heuristic based on sign language knowledge.
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