Comparing Unilateral and Bilateral Sequential TBS on prefrontal activity: a TMS-EEG study
Bibliographic record
Abstract
Background: Repetitive transcranial magnetic stimulation (rTMS) for treatment-resistant depression is effective in approximately half of those treated.Response may be related to stimulation parameters including intensity, pattern, stimulation site, and brain network engagement.Another parameter, the orientation or yaw angle of the figure-of-eight rTMS coil may also be relevant because it is thought to influence the intensity and site of stimulation.However, coil orientation has remained largely unchanged since rTMS was first used to treat depression.Methods: We performed a targeted narrative review of coil orientation in experimental, clinical and computational TMS studies.Results: We provide an illustrated overview of the TMS electric-field and its orientation-dependent interaction with underlying head tissues.Current evidence suggests that changes to coil orientation can alter the TMS electric-field and change the site of stimulation, which may not be under the coil center.Additionally, computational research suggests that coil orientation might influence brain network targeting.We therefore canvass generalized and individualized approaches to selecting rTMS coil orientation.We suggest that rTMS induced current could be directed perpendicular to local sulcal axes, as determined by average or individual anatomy.We highlight that modelling of the TMS-induced electric-field can be used to estimate the coil position and orientation for stimulating a chosen target.We further note possible implications for brain-network engagement.Conclusions: Coil orientation is an under-explored aspect of rTMS treatment.Informed adjustments to coil orientation might contribute to accurate dosing and targeting, suggesting a potential role in future research directed at improving rTMS treatment outcomes.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".