Modulation of physiological mirror activity with transcranial direct current stimulation over dorsal premotor cortex
Bibliographic record
Abstract
Humans have a natural tendency towards symmetrical movements, which rely on a distributed cortical network that allows for complex unimanual movements. Studies on healthy humans using rTMS have shown that disruption of this network, and particularly the dorsal premotor cortex (dPMC), can result in increased physiological mirror movements. The aim of the present set of experiments was to further investigate the role of dPMC in restricting motor output to the contralateral hand and determine whether physiological mirror movements could be decreased in healthy individuals. Physiological mirror movements were assessed before and after transcranial direct current stimulation (tDCS) over right and left dPMC in three conditions: bilateral, unilateral left and unilateral right stimulation. Mirror EMG activity was assessed immediately before, 0, 10 and 20 min after tDCS. Results show that physiological mirroring increased significantly in the hand ipsilateral to cathodal stimulation during bilateral stimulation of the dPMC, 10 and 20 min after stimulation compared to baseline. There was no significant modulation of physiological mirroring in the hand ipsilateral to anodal stimulation in the bilateral condition or following unilateral anodal or unilateral cathodal stimulation. The present data further implicate the dPMC in the control of unimanual hand movements and show that physiological mirroring can be increased but not decreased with dPMC tDCS.
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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) | 0.001 | 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".