Short-latency afferent inhibition determined by the sensory afferent volley
Bibliographic record
Abstract
Short-latency afferent inhibition (SAI) is characterized by the suppression of the transcranial magnetic stimulation motor evoked potential (MEP) by the cortical arrival of a somatosensory afferent volley. It remains unknown whether the magnitude of SAI reflects changes in the sensory afferent volley, similar to that observed for somatosensory evoked potentials (SEPs). The present study investigated stimulus-response relationships between sensory nerve action potentials (SNAPs), SAI, and SEPs and their interrelatedness. Experiment 1 (n = 23, age 23 ± 1.5 yr) investigated the stimulus-response profile for SEPs and SAI in the flexor carpi radialis muscle after stimulation of the mixed median nerve at the wrist using ∼25%, 50%, 75%, and 100% of the maximum SNAP and at 1.2× and 2.4× motor threshold (the latter equated to 100% of the maximum SNAP). Experiment 2 (n = 20, age 23.1 ± 2 yr) probed SEPs and SAI stimulus-response relationships after stimulation of the cutaneous digital nerve at ∼25%, 50%, 75%, and 100% of the maximum SNAP recorded at the elbow. Results indicate that, for both nerve types, SAI magnitude is dependent on the volume of the sensory afferent volley and ceases to increase once all afferent fibers within the nerve are recruited. Furthermore, for both nerve types, the magnitudes of SAI and SEPs are related such that an increase in excitation within somatosensory cortex is associated with an increase in the magnitude of afferent-induced MEP inhibition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".