Task-related enhancement in corticomotor excitability during haptic sensing with the contra- or ipsilateral hand in young and senior adults
Bibliographic record
Abstract
BACKGROUND: Haptic sensing with the fingers represents a unique class of manipulative actions, engaging motor, somatosensory and associative areas of the cortex while requiring only minimal forces and relatively simple movement patterns. Using transcranial magnetic stimulation (TMS), we investigated task-related changes in motor evoked potential (MEP) amplitude associated with unimanual haptic sensing in two related experiments. In Experiment I, we contrasted changes in the excitability of the hemisphere controlling the task hand in young and old adults under two trial conditions, i.e. when participants either touched a fine grating (smooth trials) or touched a coarse grating to detect its groove orientation (grating trials). In Experiment II, the same contrast between tasks was performed but with TMS applied over the hemisphere controlling the resting hand, while also addressing hemispheric (right vs. left) and age differences. RESULTS: In Experiment I, a main effect of trial type on MEP amplitude was detected (p = 0.001), MEPs in the task hand being ~50% larger during grating than smooth trials. No interaction with age was detected. Similar results were found for Experiment II, trial type having a large effect on MEP amplitude in the resting hand (p < 0.001) owing to selective increase in MEP size (~2.6 times greater) for grating trials. No interactions with age or side (right vs. left) were detected. CONCLUSIONS: Collectively, these results indicate that adding a haptic component to a simple unilateral finger action can elicit robust corticomotor facilitation not only in the working hemisphere but also in the opposite hemisphere. The fact that this facilitation seems well preserved with age, when task difficulty is adjusted, has some potential clinical implications.
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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 | 0.000 | 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".