Intervention-Induced Motor Cortex Plasticity in Hemiparetic Children With Perinatal Stroke
Bibliographic record
Abstract
<i>Background</i>. Clinical trials are suggesting efficacy of intensive therapy combined with brain stimulation to improve hand function in hemiparetic children with perinatal stroke. However, individual variability exists and the underlying neuroplasticity mechanisms are unknown. Exploring primary motor cortex (M1) neurophysiology, and how it changes with such interventions, may provide valuable biomarkers for advancing personalized neurorehabilitation. <i>Methods</i>. Forty-five children (age 6-19 years) with hemiparesis participated in PLASTIC CHAMPS, a blinded, sham-controlled, factorial clinical trial. All received 80 hours of goal-directed intensive upper extremity therapy. They were randomized into 4 groups: repetitive transcranial magnetic stimulation (rTMS) of contralesional M1, constraint therapy, both, or neither. Stimulus recruitment curves (SRC), short-interval intracortical inhibition (SICI), and intracortical facilitation (ICF) for lesioned and contralesional M1 were investigated using TMS. Clinical assessments including the Assisting Hand Assessment (AHA) and Canadian Occupational Performance Measure (COPM) were conducted pre- and postintervention. <i>Results</i>. All children completed the intervention and both function (AHA) and goal performance (COPM) improved with additive effects of rTMS and constraint (<i>P</i> < .01). After intervention, motor-evoked potential (MEP) amplitudes from the contralesional M1 to the less-affected hand increased (n = 16, <i>P</i> < .02). SRC from the contralesional M1 to the less-affected hand increased (n = 25, <i>P</i> < .01). SICI of the contralesional M1 to the less-affected hand decreased (n = 30, <i>P</i> < .04). No changes were observed for ICF in either hemisphere (<i>P</i> > .12). <i>Conclusion</i>. TMS applied before/after intensive neuromodulation therapies can explore M1 neurophysiology and plasticity in children with cerebral palsy. Increased MEP sizes and decreased SICI may reflect mechanisms of interventional plasticity and be potential biomarkers of individualized medicine.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.297 | 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 teacher head, 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".