Anodal tDCS improves bimanual coordination during anti-phase movements
Bibliographic record
Abstract
Cyclical bimanual movements can be characterized as in-phase (symmetrical) or anti-phase (asymmetrical) with these patterns representing elementary coordination dynamics. However, in-phase movements are more accurate and stable than anti-phase movements. If movement frequency is systematically increased during anti-phase movements, a spontaneous change (phase transition) to an in-phase pattern occurs (e.g., Kelso, 1984). Neurophysiological studies have provided converging evidence that supplementary motor area (SMA) plays a critical role in the successful performance of these patterns, especially during anti-phase movements (e.g., Serrien et al., 2002). The present experiment investigated how offline transcranial direct current stimulation (tDCS) applied over SMA affected the ability to maintain a stable relative phase. tDCS is a non-invasive neural stimulation technique that can increase (anodal) or decrease (cathodal) cortical excitability. Subjects performed metronome-paced trials of cyclical in-phase and anti-phase bimanual supination-pronation movements as oscillation frequency increased throughout each 56 s trial from 1.75 to 3.25 Hz in .25 Hz increments. Results showed no significant pre- and post-test differences for the in-phase pattern following anodal or cathodal tDCS. For the anti-phase pattern however, the mean relative phase between hands was significantly less errorful across all frequencies following anodal tDCS (p < .05). In contrast, relative phase performance at each frequency was unchanged following cathodal tDCS. These findings suggest increased activity in SMA induced by anodal tDCS can improve interlimb coordination during anti-phase patterns and adds to the accumulating evidence of the pivotal role of the SMA in bimanual coordination (e.g., Swinnen & Wenderoth, 2004).Acknowledgments: Supported by NSERC (ANC)
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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".