Variability in TMS-EEG response can partially be described by the phase of ongoing brain oscillation
Bibliographic record
Abstract
frequency (~300 Hz) oscillations in GP and STN.This evoked activity resembled a sinusoid, growing in the shape of a sigmoid throughout the burst, and decaying exponentially after the last burst stimulation.This novel sigmoid-exponential-sinusoid (SES) model successfully fit the data with R-squared values of up to 0.9.Theories of the origin of this phenomenon involve local patterns of inhibition and excitation in STN, or interactions between STN and connected structures, such as the pallidum.Our detected high-frequency oscillations in STN and GP from pallidal stimulation, complementing those previously observed from STN stimulation, support the hypothesis that the phenomenon is generated by a loop involving both structures.No oscillatory response was detected when stimulating or recording in thalamus.This implies that the phenomenon is likely unique to BG, making it a promising biomarker.It has also been suggested as a possible feedback signal for closed-loop DBS, which our SES model parameters provide convenient quantitative measurements for.Finally, our findings in a dystonic patient imply that this phenomenon is not unique to Parkinson's disease, but likely generalizable to other movement disorders and perhaps even healthy subjects.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".