Effector-independent reduction in choice reaction time following bi-hemispheric transcranial direct current stimulation over motor cortex
Bibliographic record
Abstract
Increased reaction times (RT) during choice-RT tasks stem from a requirement for additional processing as well as reduced motor-specific preparatory activation. Transcranial direct current stimulation (tDCS) can modulate primary motor cortex excitability, increasing (anodal stimulation) or decreasing (cathodal stimulation) excitability in underlying cortical tissue. The present study investigated whether lateralized differences in choice-RT would result from the concurrent modulation of left and right motor cortices using bi-hemispheric tDCS. Participants completed a choice-RT task requiring either a left or right wrist extension. In forced-choice trials an illuminated target indicated the required response, whereas in free-choice trials participants freely selected either response upon illumination of a central fixation. Following a pre-test trial block, offline bi-hemispheric tDCS (1 mA) was applied over the left and right motor cortices for 10 minutes, which was followed by a post-tDCS block of RT trials. Twelve participants completed three experimental sessions, two with real tDCS (anode right, anode left), as well as a sham tDCS session. Post-tDCS results showed faster RTs for both right and left responses irrespective of tDCS polarity during forced-choice trials, while sham tDCS had no effect. In contrast, no stimulation-related RT or response selection differences were observed in free-choice trials. The present study shows evidence of an effector-independent speeding of response initiation in a forced-choice RT task following bi-hemispheric tDCS and yields novel information regarding the functional effect of bi-hemispheric 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 | 0.001 |
| 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".