Anodal transcranial direct current stimulation applied over the supplementary motor area delays spontaneous antiphase-to-in-phase transitions
Bibliographic record
Abstract
Coordinated bimanual oscillatory movements often involve one of two intrinsically stable phasing relationships characterized as in-phase (symmetrical) or antiphase (asymmetrical). The in-phase mode is typically more stable than antiphase, and if movement frequency is increasing during antiphase movements, a spontaneous transition to the in-phase pattern occurs. There is converging neurophysiological evidence that the supplementary motor area (SMA) plays a critical role in the successful performance of these patterns, especially during antiphase movements. We investigated whether modulating the excitability of the SMA via offline transcranial direct current stimulation (tDCS) would delay the onset of anti-to-in-phase transitions. Participants completed two sessions (separated by ∼48 h), each consisting of a pre- and post-tDCS block in which they performed metronome-paced trials of rhythmic in- and antiphase bimanual supination-pronation movements as target oscillation frequency was systematically increased. Anodal or cathodal tDCS was applied over the SMA between the pre- and post-tDCS blocks in each session. Following anodal tDCS, participants performed the antiphase pattern with increased accuracy and stability and were able to maintain the coordination pattern at a higher oscillation frequency. Antiphase performance was unchanged following cathodal tDCS, and neither tDCS polarity affected the in-phase mode. Our findings suggest increased SMA excitability induced by anodal tDCS can improve antiphase performance and adds to the accumulating evidence of the pivotal role of the SMA in interlimb coordination.
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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".