Rehabilitation‐induced brain changes detected through magnetic resonance imaging in children with neurodevelopmental disorders: A systematic review
Bibliographic record
Abstract
AIM: The aim of this study was to systematically review evidence about rehabilitation-induced neuroplasticity measured by magnetic resonance imaging (MRI) in children with neurodevelopmental disorders. METHOD: The following databases were searched: MEDLINE, EMBASE, CINAHL, and PsycINFO. Two independent reviewers screened articles according to inclusion criteria: (1) peer-review study published in a scientific journal; (2) studies that evaluated a rehabilitation-based intervention; (3) participants aged less than 19 years with a neurodevelopmental disorder; and (4) studies that used at least one MRI modality as an outcome measure. Twenty-seven studies met the criteria for the review and their quality was assessed by two independent reviewers using the Effective Public Health Practice Project Quality Assessment Tool. RESULTS: Based on an assessment of bias and overall quality, 11% of the papers were rated as strong; 30% moderate; and 59% weak. Outcomes were categorized into structural connectivity, functional connectivity, cortical activation, and structural volume. Cortical activation and structural connectivity were the most commonly reported measures. Most studies were able to identify brain changes in children with neurodevelopmental disorders after therapy. INTERPRETATIONS: Rehabilitation is shown to induce MRI-detectable neuroplastic changes in children with neurodevelopmental disorders. Structural connectivity might need greater intensity and/or duration of intervention to induce change.
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".