Modulation of Short-Latency Afferent Inhibition Depends on Digit and Task-Relevance
Bibliographic record
Abstract
Short-latency afferent inhibition (SAI) occurs when a single transcranial magnetic stimulation (TMS) pulse delivered over the primary motor cortex is preceded by peripheral electrical nerve stimulation at a short inter-stimulus interval (∼ 20-28 ms). SAI has been extensively examined at rest, but few studies have examined how this circuit functions in the context of performing a motor task and if this circuit may contribute to surround inhibition. The present study investigated SAI in a muscle involved versus uninvolved in a motor task and specifically during three pre-movement phases; two movement preparation phases between a "warning" and "go" cue and one movement initiation phase between a "go" cue and EMG onset. SAI was tested in the first dorsal interosseous (FDI) and abductor digiti minimi (ADM) muscles in twelve individuals. In a second experiment, the origin of SAI modulation was investigated by measuring H-reflex amplitudes from FDI and ADM during the motor task. The data indicate that changes in SAI occurred predominantly in the movement initiation phase during which SAI modulation depended on the specific digit involved. Specifically, the greatest reduction in SAI occurred when FDI was involved in the task. In contrast, these effects were not present in ADM. Changes in SAI were primarily mediated via supraspinal mechanisms during movement preparation, while both supraspinal and spinal mechanisms contributed to SAI reduction during movement initiation.
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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".