Relationship between transcranial magnetic stimulation measures of intracortical inhibition and spectroscopy measures of GABA and glutamate+glutamine
Bibliographic record
Abstract
Transcranial magnetic stimulation (TMS) can provide an index of intracortical excitability/inhibition balance. However, the neurochemical substrate of these measures remains unclear. Pharmacological studies suggest the involvement of GABAA and GABAB receptors in TMS protocols aimed at measuring intracortical inhibition, but this link remains inferential. Proton magnetic resonance spectroscopy ((1)H-MRS) permits measurement of GABA and glutamate + glutamine (Glx) concentrations in the human brain and might help in the direct empirical assessment of the relationship between TMS inhibitory measures and neurotransmitter concentrations. In the present study, MRS-derived relative concentrations of GABA and Glx measured in the left M1 of healthy participants were correlated with TMS measures of intracortical inhibition. Glx levels were found to correlate positively with TMS-induced silent period duration, whereas no correlation was found between GABA concentration and TMS measures. The present data demonstrate that specific TMS measures of intracortical inhibition are linked to shifts in cortical Glx, rather than GABA neurotransmitter levels. Glutamate might specifically interact with GABAB receptors, where higher MRS-derived Glx concentrations seem to be linked to higher levels of receptor activity.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".