Beneficial effects of a music listening intervention on neural speech processing in 0–28‐month‐old children at risk for dyslexia
Bibliographic record
Abstract
Familial risk for developmental dyslexia can compromise auditory and speech processing and subsequent language and literacy development. According to the phonological deficit theory, supporting phonological development during the sensitive infancy period could prevent or ameliorate future dyslexic symptoms. Music is an established method for supporting auditory and speech processing and even language and literacy, but no previous studies have investigated its benefits for infants at risk for developmental language and reading disorders. We pseudo-randomized N∼150 infants at risk for dyslexia to vocal or instrumental music listening interventions at 0-6 months, or to a no-intervention control group. Music listening was used as an easy-to-administer, cost-effective intervention in early infancy. Mismatch responses (MMRs) elicited by speech-sound changes were recorded with electroencephalogram (EEG) before (at birth) and after (at 6 months) the intervention and at a 28 months follow-up. We expected particularly the vocal intervention to promote phonological development, evidenced by enhanced speech-sound MMRs and their fast maturation. We found enhanced positive MMR amplitudes in the vocal music listening intervention group after but not prior to the intervention. Other music activities reported by parents did not differ between the three groups, indicating that the group effects were attributable to the intervention. The results speak for the use of vocal music in early infancy to support speech processing and subsequent language development in infants at developmental risk. RESEARCH HIGHLIGHTS: Dyslexia-risk infants were pseudo-randomly assigned to a vocal or instrumental music listening intervention at home from birth to 6 months of age. Neural mismatch responses (MMRs) to speech-sound changes were enhanced in the vocal music intervention group after but not prior to the intervention. Even passive vocal music listening in early infancy can support phonological development known to be deficient in dyslexia-risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".