A dose-response characterization of transcranial magnetic stimulation intensity and evoked potential amplitude in the dorsolateral prefrontal cortex
Bibliographic record
Abstract
By combining transcranial magnetic stimulation (TMS) with electroencephalography, human cortical circuits can be directly interrogated. The resulting electrical trace contains TMS-evoked potential (TEP) components, and it is not known whether the amplitudes of these components are stimulus intensity dependent. We examined this in the left dorsolateral prefrontal cortex in nineteen healthy adult participants and extracted TEP amplitudes for the N40, P60, N120, and P200 components at 110%, 120%, and 130% of resting motor threshold (RMT). To probe plasticity of putative stimulus intensity dose-response relationships, this was repeated after participants received intermittent theta burst stimulation (iTBS; 600 pulses, 80% RMT). The amplitude of the N120 and P200 components exhibited a stimulus intensity dose-response relationship, however the N40 and P60 components did not. After iTBS, the N40 and P60 components continued to exhibit a lack of stimulus intensity dose-dependency, and the P200 dose-response was unchanged. In the N120 component, however, we saw evidence of change within the stimulus intensity dose-dependent relationship characterized by a decrease in absolute peak amplitudes at lower stimulus intensities. These data suggest that TEP components have heterogeneous dose-response relationships, with implications for standardizing and harmonizing methods across experiments. Moreover, the selective modification of the N120 dose-response relationship may provide a novel marker for iTBS plasticity in health and disease.
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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 | 0.002 |
| 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) | 0.001 | 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".