White matter but not grey matter predicts change in reading skills after intervention
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.017 | 0.015 |
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 it