Continuous theta-burst stimulation to primary motor cortex reveals asymmetric compensation for sensory attenuation in bimanual repetitive force production
Bibliographic record
Abstract
Studies of fingertip force production have shown that self-produced forces are perceived as weaker than externally generated forces. This is due to mechanisms of sensory reafference where the comparison between predicted and actual sensory feedback results in attenuated perceptions of self-generated forces. Without an external reference to calibrate attenuated performance judgments, a compensatory overproduction of force is exhibited. It remains unclear whether the force overproduction seen in the absence of visual reference stimuli differs when forces are produced bimanually. We studied performance of two versions of a bimanual sequential force production task compared with each hand performing the task unimanually. When the task goal was shared, force series produced by each hand in bimanual conditions were found to be uncorrelated. When the bimanual task required each hand to reach a target force level, we found asymmetries in the degree of force overproduction between the hands following visual feedback removal. Unilateral continuous theta-burst stimulation of the left primary motor cortex yielded a selective reduction of force overproduction in the hand contralateral to stimulation by disrupting sensory reafference processes. While variability was lower in bimanual trials when the task goal was shared, this influence of hand condition disappeared when the target force level was to be reached by each hand simultaneously. Our findings strengthen the notion that force control in bimanual action is less tightly coupled than other mechanisms of bimanual motor control and show that this effector specificity may be extended to the processing and compensation for mechanisms of sensory reafference.
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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) | 0.001 | 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".