Enhancement of Temporal Processing via Transcutaneous Vagus Nerve Stimulation
Bibliographic record
Abstract
Abstract Background The vagus nerve, a crucial component of the parasympathetic nervous system, serves as a vital communication link between the brain and body. Recent studies indicate that auricular stimulation of the vagus nerve can influence executive functions by increasing activity in brain regions like the prefrontal cortex. While prefrontal areas are associated with temporal processing, it remains unclear whether vagus nerve stimulation can also impact time perception. Hypothesis The stimulation of the vagus nerve via its auricular branch may enhance performance in temporal processing by boosting activities in prefrontal brain areas related to temporal processing. Methods Temporal processing abilities were assessed using an anisochrony detection task, where participants identified temporal irregularities in otherwise isochronous sequences while undergoing transcutaneous Vagus Nerve Stimulation (tVNS) or sham stimulation. Results The results of this study, for the first time, revealed that participants could recognize smaller temporal shifts when the vagus nerve was stimulated, compared to the sham condition. Conclusion The findings suggest that vagus nerve stimulation modulates temporal processing, supporting the notion that transcutaneous stimulation of the vagus nerve can influence cognitive functions related to temporal processing, possibly by enhancing prefrontal activities.
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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 | 0.000 |
| 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) | 0.002 | 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".