Does neural oscillatory coupling during morphological processing differentiate children with and without reading difficulties?
Bibliographic record
Abstract
While reading, children use their morphological awareness to help facilitate word recognition; this awareness is anomalous in children with reading difficulty. I examined the morphological processing of 33 children; 13 with reading difficulty (RD) and 20 typical readers (TR). A lexical decision task was used to examine how orthographic and semantic word properties facilitate word recognition in these groups. Behavioural methods showed faster response times by both groups in conditions where primes reflected a morpho-semantic, compared to morpho-orthographic suffix type, and where primes were related to target words. Using electrophysiological measures, the power and oscillatory coupling were examined of three EEG brain frequencies, delta, theta, and gamma, to better understand the neural correlates reflecting morphological awareness during word recognition. While no group differences emerged in the behavioural results, electrophysiological results indicated neurological differences between groups, reader group differences in delta, theta and gamma power, as well as morphological condition differences in power. Most importantly, the examination of theta/gamma phase-amplitude coupling revealed reading ability differences, which provided evidence of the RD group’s greater use of top-down activation while segmenting morphologically complex words. This study helps refine our understanding of the neurocognitive mechanisms underlying morphological awareness abilities in children with RD and provides neurological evidence for their over-reliance on semantic properties during word recognition.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".