Bilateral Motor Cortex Plasticity in Individuals With Chronic Stroke, Induced by Paired Associative Stimulation
Bibliographic record
Abstract
BACKGROUND: In the chronic phase after stroke, cortical excitability differs between the cerebral hemispheres; the magnitude of this asymmetry depends on degree of motor impairment. It is unclear whether these asymmetries also affect capacity for plasticity in corticospinal tract excitability or whether hemispheric differences in plasticity are related to chronic sensorimotor impairment. METHODS: Response to paired associative stimulation (PAS) was assessed bilaterally in 22 individuals with chronic hemiparesis. Corticospinal excitability was measured as the area under the motor-evoked potential (MEP) recruitment curve (AUC) at baseline, 5 minutes, and 30 minutes post-PAS. Percentage change in contralesional AUC was calculated and correlated with paretic motor and somatosensory impairment scores. RESULTS: PAS induced a significant increase in AUC in the contralesional hemisphere ( P = .041); in the ipsilesional hemisphere, there was no significant effect of PAS ( P = .073). Contralesional AUC showed significantly greater change in individuals without an ipsilesional MEP ( P = .029). Percentage change in contralesional AUC between baseline and 5 m post-PAS correlated significantly with FM score ( r = -0.443; P = .039) and monofilament thresholds ( r = 0.444, P = .044). DISCUSSION: There are differential responses to PAS within each cerebral hemisphere. Contralesional plasticity was increased in individuals with more severe hemiparesis, indicated by both the absence of an ipsilesional MEP and a greater degree of motor and somatosensory impairment. These data support a body of research showing compensatory changes in the contralesional hemisphere after stroke; new therapies for individuals with chronic stroke could exploit contralesional plasticity to help restore function.
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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 | 0.000 |
| 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) | 0.002 | 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".