Reading ability in both deaf and hearing adults is linked to neural representations of abstract phonology derived from visual speech
Bibliographic record
Abstract
Abstract Reading is central to academic and vocational success. Some deaf children face reading challenges due to limited access to spoken or signed language. Robust phonological representations are key to reading development in hearing children. Spoken language phonology may be one of many contributors to reading development in deaf children. Indeed, speechreading ability correlates with reading skill in both deaf and hearing individuals, suggesting it is linked to reading development regardless of hearing status. Further support for this hypothesis would be provided by evidence that similar neural representations of speech phonology are evoked by visual speech and other language forms (auditory speech and text), and that these neural representations are related to reading proficiency. We used fMRI and Representational Similarity Analysis (RSA) to identify shared neural representations of spoken language phonological structure. A group of deaf adult participants (N=22), with a mixture of sign language and spoken language backgrounds and reading abilities, were presented with single lexical items as visual speech and dynamic text (cursive text, revealed letter-by-letter to promote a phonological reading strategy). Adult hearing participants (N=25) were presented with the same words, but as visual speech and auditory speech. Shared neural representations of phonological structure of English words were found in each group in the superior and middle temporal cortex (STC/MTC) and these abstract representations were more similar across different language forms in better readers. Our data provide neurobiological evidence of the contribution of visual speech to abstract phonological representations of spoken language, that relate to reading proficiency, in both deaf and hearing adults. Significance Statement Reading is an essential skill, yet some deaf children face reading challenges due to reduced access to signed or spoken language. In hearing children, successful reading depends on abstract phonological representations, but whether spoken language phonology relates to reading in deaf individuals remains unclear. Using fMRI and RSA, we show that deaf and hearing adults recruit neural representations of phonology that are shared by visual speech and other language forms (visual/auditory speech in hearing; visual speech/dynamic text in deaf) in the superior and middle temporal cortex. Critically, greater cross-modal alignment of neural representations of phonological structure was associated with better reading in both groups. These findings provide neurobiological evidence that visual speech contributes to phonological representations that relate to reading, regardless of hearing status.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".