Effects of short interval intracortical inhibition and intracortical facilitation on short interval intracortical facilitation in human primary motor cortex
Bibliographic record
Abstract
Short interval intracortical facilitation (SICF) can be elicited by transcranial magnetic stimulation (TMS) of the motor cortex (M1) with a suprathreshold first stimulus (S1) followed by a subthreshold second stimulus (S2). SICF occurs at three distinct phases and is likely to be related to the generation of indirect (I) waves. Short interval intracortical inhibition (SICI) is an inhibitory phenomenon and intracortical facilitation (ICF) is an excitatory phenomenon occurring in the M1 that can be studied with TMS. We studied the interactions between SICI/ICF and SICF in 17 healthy subjects. Six experiments were conducted. The first experiment examined the effects of different S1 intensities on SICI, ICF and SICF at three peaks. The effects of SICI on SICF were tested by a triple-pulse TMS protocol in the second experiment. We performed Experiments 3-5 to further test the interactions between SICI and SICF with various strengths of SICI, at SICF peaks and troughs, and with SICF generated by different current direction which preferentially generates late I waves. The effects of ICF on SICF were examined in Experiment 6. The results showed that ICF and SICF decreased whereas SICI increased with higher S1 intensities. SICI facilitated SICF mediated by late I waves both at the peaks and the troughs of SICF. The increase of SICF in the presence of SICI correlated to the strength of SICI. ICF decreased the third peak of SICF. We conclude that SICI facilitates SICF at neuronal circuits responsible for generating late I waves through disinhibition, while ICF may have the opposite effects.
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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".