EEG reveals temporal dynamics of tms cortical recovery
Bibliographic record
Abstract
Transcranial magnetic stimulation (TMS) has been used to investigate cortical function in healthy subjects for decades. However, prolonged disruptive effects of of a single pulse of TMS has not been investigated. Currently, it appears there is no standardized time period between TMS stimulation in order to limit interference between trials. In this experiment we used a combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) techniques to examine the temporal and spatial characteristics of an evoked potential across the brain. Subjects were fitted with an EEG cap according to standard 10-20 EEG system. TMS stimulation was applied with an MRI-guided sterotactic system to ensure that the appropriate cortical areas are accurately stimulated. Motor threshold (MT) is found via movement evoked potential (MEP) of the first dorsal interosseous muscle and was used to sample subjects at threshold and sub-threshold values. Multiple stimulation sites are sampled in order to compare TMS effects on different areas of the brain. The experiment session will include a third sample of sham TMS is included in the testing protocol in order to eliminate auditory artifacts TMS present in EEG recordings. The resulting findings will facilitate future research in TMS by providing an appropriate time interval to negate interference between stimulations.
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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) | 0.003 | 0.001 |
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".