Selective increase in corticospinal excitability in the context of tactile exploration
Bibliographic record
Abstract
In this study, we compared changes in corticomotor excitability under various task conditions engaging the index finger of each hand. Functional demands were varied, from simple execution to demanding sensory exploration. In a first experiment, we contrasted facilitation in the first dorsal interosseus (FDI) by monitoring changes in motor evoked potentials (MEPs) when participants (young adults, n = 18) performed either a simple button pressing (BP) task or a more demanding tactile exploration (TE) task (i.e., discrimination of raised letters). This experiment showed a large effect of task conditions (p < 0.01) on MEP amplitude but no effect of "Hand", while latency measurements were unchanged. In fact, MEPs were on average 40% larger during TE (2410 +/- 1358 microV) than during BP (1670 +/- 1477 microV). The two tasks produced, however, different patterns of electromyographic (EMG) activity, which could have accounted for some of the differences observed. A second experimental session involved a subset of participants (10/18) tested in third task condition: finger movement (FM). The latter task consisted of scanning a smooth surface with the tip of the index finger to reproduce the movements seen with the TE task. The addition of this third condition task confirmed that MEP facilitation seen during TE reflected task-specific influences and not differences in background EMG activity. These results, altogether, provide further insights into the effect of task conditions on corticomotor excitability. Our findings, in particular, stress the importance of behavioural context and tactile exploration in leading to selective increase in corticomotor excitability during finger movements.
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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) | 0.001 | 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".