Effects of static transcranial magnetic stimulation over right parietal cortex on visuomotor adaptation
Bibliographic record
Abstract
The parietal cortex is thought to play a crucial role in visuomotor adaptation. Recently, our laboratory has provided evidence that the parietal contribution to visuomotor adaptation may be lateralized, such that adaptation to perturbed visual feedback presented to the left of gaze may more strongly solicit the right parietal hemisphere and vice versa. The purpose of this study was to test this hypothesis with inhibitory static transcranial magnetic stimulation (STMS). Briefly, during an acquisition phase (200 trials) participants made reaching movements towards visual targets located either to the left or right of gaze while learning to compensate for a 30° visuomotor rotation. Implicit adaptation was then assessed with a retention test without online visual feedback. In the STMS group (N=9) a cylindrical neodymium magnet was positioned over the right parietal cortex, whereas in the placebo group (PLA, N=10), a non-magnetic nickel cylinder was placed over the same area. Given its position, it was hypothesised that STMS would selectively impair implicit adaptation to targets located to the left of gaze. Notably, our results refute this hypothesis, as retention was not significantly different between STMS and PLA at right or left target locations. During the last 40 trials of acquisition, however, STMS compensated for less of the visuomotor rotation compared to PLA (p=0.02), and this was solely true for targets located to the left of gaze. These preliminary findings suggest that the parietal hemisphere contralateral to visual feedback plays a role in compensating for, but not implicitly adapting to, a visuomotor rotation.
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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".