The Use of Direct Current Stimulation to Investigate the Role of Each Hemisphere in Motor Learning of Reaching Task
Bibliographic record
Abstract
Introduction: Transcranial Direct Current Stimulation (tDCS) can improve or impair the function of the brain.This has turned tDCS into a tool that can be used for evaluation of hemispheric specialization in motor programming and final position accuracy, as components of motor control and learning.Materials and Methods: Two different studies were designed.53 male students (21.34±1.61years) and 43 male students (20.442±1.578years) were participated in the first and second studies, respectively.Participants were randomly assigned into four groups.C3 /C4 and F3/F4 areas were stimulated with the 2mA current in the first and second studies, respectively.The Repeated Measure test was used to analyze data.Results: In the first experiment, left M1 group (left anode/right cathode stimulation) significantly improved motor programming compared to the other groups.In the second experiment, the right dorsolateral prefrontal cortex group (right cathode/left anode) significantly decreased final position accuracy compared to the other groups.Conclusion:Our data suggested that the left hemisphere is specialized for motor programming whereas the right hemisphere is specialized for final position accuracy.These results are interpretable with hybrid motor control hypothesis.
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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".