Recovery of hand function after stroke: separable systems for finger strength and control
Bibliographic record
Abstract
Abstract Loss of hand function after stroke is a major cause of long-term disability. Hand function can be partitioned into strength and independent control of fingers (individuation). Here we developed a novel paradigm, which independently quantifies these two aspects of hand function, to track hand recovery in 54 patients with hemiparesis over the first year after their stroke. Most recovery of both strength and individuation occurred in the first three months after stroke. Improvement in strength and individuation were tightly correlated up to a strength level of approximately 60% of the unaffected side. Beyond this threshold, further gains in strength were not accompanied by improvements in individuation. Any observed improvements in individuation beyond the 60% threshold were attributable instead to a second independent stable factor. Lesion analysis revealed that damage to the hand area in motor cortex and the corticospinal tract (CST) correlated more with individuation than with strength. CST involvement correlated with individuation even after factoring out the strength-individuation correlation. The most parsimonious explanation for these behavioral and lesion-based findings is that most strength recovery, along with some individuation, can be attributed to descending systems other than the CST, whereas further recovery of individuation is CST dependent.
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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 | 0.001 |
| 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 | 0.000 |
| 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".