White matter but not grey matter predicts change in reading skills after intervention
Bibliographic record
Abstract
This study examined changes in white matter microstructure and grey matter volume, cortical thickness, and cortical surface area before and after reading intervention. Participants included 22 average readers and 13 dyslexic readers (8-9 years old in third grade); the dyslexic readers were enrolled in reading intervention programs at their elementary school. Participants completed scans of diffusion tensor imaging and T1-weighted MRI before and after 3 months of instruction. An a priori region of interest (ROI) analysis was used. Dyslexic readers, compared to average readers, showed higher mean diffusivity in white matter ROIs including bilateral inferior frontal, bilateral insula, left superior temporal, and right supramarginal gyri across time points. Dyslexic readers also had thicker cortex in left fusiform and bilateral supramarginal gyri; whereas, average readers had greater surface area in right fusiform across time. There were no significant changes in white or grey matter following intervention; however, mean diffusivity in the right hemisphere was associated with reading gains over time. White matter organization in the right hemisphere predicts reading changes, and dyslexic readers may have persistent differences in white and grey matter due to ongoing reading deficits.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".