Sensorimotor adaptation changes the neural coding of somatosensory stimuli
Bibliographic record
Abstract
Motor learning is reflected in changes to the brain's functional organization as a result of experience. We show here that these changes are not limited to motor areas of the brain and indeed that motor learning also changes sensory systems. We test for plasticity in sensory systems using somatosensory evoked potentials (SEPs). A robotic device is used to elicit somatosensory inputs by displacing the arm in the direction of applied force during learning. We observe that following learning there are short latency changes to the response in somatosensory areas of the brain that are reliably correlated with the magnitude of motor learning: subjects who learn more show greater changes in SEP magnitude. The effects we observe are tied to motor learning. When the limb is displaced passively, such that subjects experience similar movements but without experiencing learning, no changes in the evoked response are observed. Sensorimotor adaptation thus alters the neural coding of somatosensory stimuli.
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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".