Impact of galvanic vestibular stimulation electrode current density on brain current flow patterns: Does electrode size matter?
Bibliographic record
Abstract
BACKGROUND: Galvanic vestibular stimulation (GVS) uses at least one electrode placed on the mastoid process with one or multiple placed over other head areas to stimulate the vestibular system. The exact electrode size used is not given much importance in the literature and has not been reported in several studies. In a previous study, we compared the clinical effects of using different electrode sizes (3 cm2 and 35 cm2) with placebo but with the same injected current, on postural control. We observed significant improvement using the smaller size electrode but not with the bigger size electrode. The goal of this study was to simulate the current flow patterns with the intent to shed light and potentially explain the experimental outcome. METHODS: We used an ultra-high-resolution structural dataset and developed a model to simulate the application of different electrode sizes. We considered current flow in the brain and in the vestibular labyrinth. RESULTS: Our simulation results verified the focality increase using smaller electrodes that we postulated as the main reason for our clinical effect. The use of smaller size electrodes in combination with the montage employed also result in higher induced electric field (E-field) in the brain. CONCLUSIONS: Electrode size and related current density is a critical parameter to characterize any GVS administration as the choice impacts the induced E-field. It is evident that the higher induced E-field likely contributed to the clinical outcome reported in our prior study.
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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 | 0.001 | 0.007 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".