Neurophysiological basis of manual force asymmetries in young and senior adults
Bibliographic record
Abstract
In this study, we investigated age differences in manual force production to explore their neurophysiological basis. Manual pinching and gripping forces were first measured during unilateral and bilateral efforts in two groups of right-handed adults (young, n = 12, senior, n = 11). Then, transcranial magnetic stimulation (TMS) was applied to each hemisphere to assess central motor inhibition via the contralateral and ipsilateral silent period (cSP, iSP). Laterality quotients (LQs) were computed to determine asymmetries for unimanual strength tests and hemispheric asymmetries in TMS measures. Bilateral indices (BLI) were computed to assess the bilateral force deficit (BFD). During unilateral efforts, both young and senior participants exhibited similar degrees of asymmetry. Similarly, no age difference was detected when comparing LQs derived from TMS measures. During bilateral efforts, although BLI tended to be lower in seniors, no age difference was detected. Asymmetry in strength and BLI showed no association with hemispheric asymmetry in TMS measures, except for the asymmetry in pinch strength, which was associated with asymmetry in the iSP duration. These observations confirm that asymmetries in manual strength and BFD are little affected by age. Also, our results show that hemispheric asymmetries in transcallosal inhibition are associated with pinch strength asymmetry.
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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) | 0.003 | 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".