Turbocharging the "go" horse: Anodal TDCS results in early response initiation in a stop-signal anticipation-timing task
Bibliographic record
Abstract
Previous research has shown that the supplementary motor area (SMA) plays a critical role in the inhibition of movement. Recently it was shown that applying non-invasive transcranial direct current stimulation (tDCS) over the SMA affected participants' ability to inhibit their movement in a stop-signal reaction time task (Hsu et al. 2011). It was of interest in the current study whether modulating SMA excitability using tDCS would have similar effects in a stop-signal anticipation-timing task. Participants performed 2 sessions each consisting of both a pre- and post-test block of 160 trials in which they were instructed to extend their wrist concurrently with the arrival of a pointer to a target (i.e., a clock hand reaching a set position). In 20% of trials (stop trials) the pointer stopped 80, 110, 140, 170, or 200 ms prior to the target, and on these trials participants were instructed to inhibit their movement if possible. Anodal and cathodal tDCS sessions were applied for each participant, separated by at least 48 hours, between the pre- and post-tests. No change in the proportion of successfully inhibited movements on stop trials was found in post-tests for either tDCS polarity compared to pre-test (all p's > .05). However, anodal tDCS resulted in the early onset of movements in control trials with respect to the target (p = .028). These results suggest that the SMA may not have a crucial role in inhibiting anticipated movements, but may be more involved in initiation.Acknowledgments: Supported by NSERC
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".