Motor cortex excitability and inhibitory imbalance in autism spectrum disorder assessed with transcranial magnetic stimulation: a systematic review
Bibliographic record
Abstract
Cortical excitation/inhibition (E/I) imbalances contribute to various clinical symptoms observed in autism spectrum disorder (ASD). However, the detailed pathophysiologic underpinning of E/I imbalance remains uncertain. Transcranial magnetic stimulation (TMS) motor-evoked potentials (MEP) are a non-invasive tool for examining cortical inhibition in ASD. Here, we conducted a systematic review on TMS neurophysiology in motor cortex (M1) such as MEPs and short-interval intracortical inhibition (SICI) between individuals with ASD and controls. Out of 538 initial records, we identified six articles. Five studies measured MEP, where four studies measured SICI. There were no differences in MEP amplitudes between the two groups, whereas SICI was likely to be reduced in individuals with ASD compared with controls. Notably, SICI largely reflects GABA(A) receptor-mediated function. Conversely, other magnetic resonance spectroscopy and postmortem methodologies assess GABA levels. The present review demonstrated that there may be neurophysiological deficits in GABA receptor-mediated function in ASD. In conclusion, reduced GABAergic function in the neural circuits could underlie the E/I imbalance in ASD, which may be related to the pathophysiology of clinical symptoms of ASD. Therefore, a novel treatment that targets the neural circuits related to GABA(A) receptor-mediated function in regions involved in the pathophysiology of ASD may be promising.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".