Reversal of visual feedback modulates somatosensory plasticity
Bibliographic record
Abstract
Abstract Reversed visual feedback during unimanual training increases transfer of skills to the opposite untrained hand and modulates plasticity in motor areas of the brain. However, it is unclear if unimanual training with reversed visual feedback also affects somatosensory areas. Here we manipulated visual input during unimanual training using left-right optical reversing spectacles and tested whether unimanual training with reversed vision modulates somatosensory cortical excitability to facilitate motor performance. Thirty participants practiced a unimanual ball-rotation task using the right hand with either left-right reversed vision (incongruent visual and somatosensory feedback) or direct vision (congruent feedback) of the moving hand. We estimated cortical excitability in primary somatosensory cortex (S1) before and after unimanual training by measuring somatosensory evoked potentials (SEPs). This was done by electrically stimulating the median nerve in the wrist while participants rested, and recording potentials over both hemispheres using electroencephalography. Performance of the ball-rotation task improved for both the right (trained) and left (untrained) hand after training across both direct and reversed vision conditions. Participants with direct vision of the right hand during training showed SEPs amplitudes increased bilaterally. In contrast, participants in the reversed visual condition showed attenuated SEPs following training. The results suggest that cortical suppression of S1 activity supports skilled motor performance after unimanual training with reversed vision, presumably by sensory gating of afferent signals from the movement. This finding provides insight into the mechanisms by which visual input interacts with the sensorimotor system and induces neuroplastic changes in S1 to support skilled motor performance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".