Cortical Inhibition in Motor and Non-Motor Regions: A Combined TMS-EEG Study
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Bibliographic record
Abstract
A number of studies using paired pulse transcranial magnetic stimulation (TMS) have demonstrated that cortical inhibition (CI) of the motor cortex can be recorded and also gauged through surface electromyography. However, recording CI from other brain regions that are more directly related with the pathophysiology of some neurologic and psychiatric disorders (e.g., dorsolateral prefrontal cortex (DLPFC) in schizophrenia) was previously fraught with technical difficulties. This study was therefore designed to examine, through a combination of TMS with EEG, whether CI could be measured directly from the motor cortex, DLPFC, and another non-motor region. To index CI, long interval cortical inhibition (LICI; a TMS paradigm) was used in the motor cortex and DLPFC in 14 healthy subjects, and in the parietal lobe in 5 of those subjects. In the motor cortex, LICI resulted in a significant suppression in mean cortical evoked activity on EEG (37.31 +/- 47.51%). In the DLPFC, LICI resulted in a significant suppression (32.45 +/- 47.86%) in mean cortical evoked activity and did not correlate with LICI in the motor cortex although they did not significantly differ. In the parietal lobe, LICI resulted in significant suppression (47.76 +/- 44.70%) in mean cortical evoked activity. In conclusion, CI in the dorsolateral prefrontal cortex, motor cortex and parietal cortex were similar at 120% of motor threshold. These data suggest that CI can be recorded by combining TMS with EEG and may facilitate future research attempting to ascertain the role of CI in the pathophysiology of several neurologic and psychiatric disorders.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| 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 it