Effect of long interval interhemispheric inhibition on intracortical inhibitory and facilitatory circuits
Bibliographic record
Abstract
Stimulation of the primary motor cortex (M1) of one hemisphere of the brain inhibits the opposite M1, a process known as interhemispheric inhibition (IHI). An early phase of IHI peaks at about approximately 10 ms after stimulation of the opposite hemisphere and is termed short latency interhemispheric inhibition (SIHI). A later phase peaks at about 40 ms and has been termed long latency interhemispheric inhibition (LIHI). The objective of the present study is to test how LIHI interacts with cortical inhibitory and facilitatory circuits, including short interval intracortical inhibition (SICI), intracortical facilitation (ICF) and long interval intracortical inhibition (LICI). We studied 10 healthy volunteers. LIHI from right to left hemisphere was elicited by stimulating the right M1 at an interstimulus interval (ISI) of 40 ms before stimulation of the left M1. Conditioning and test stimuli to elicit SICI, ICF and LICI were given to left M1. The effects of different sizes of test motor-evoked potential (MEP amplitudes; 0.2, 1 and 2 mV) were examined for SICI, ICF, LICI and LIHI. Using paired-pulse and triple-pulse protocols, how LIHI interacts with SICI, ICF and LICI were investigated. We found SICI increased, while LICI and LIHI decreased with increasing test MEP amplitude. The presence of LIHI did not change the degree of SICI and intracortical facilitation (ICF), and their effects of these circuits were additive. On the other hand, LICI and LIHI were reduced in the presence of each other. We conclude that different sets of cortical neurons mediate LIHI, SICI, ICF and LICI. GABA(B)-mediated LICI and LIHI have inhibitory interactions with each other while LIHI has an additive effect with GABA(A)-mediated SICI.
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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 | 0.001 |
| 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 | 0.001 |
| 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".