The Consolidation of Newly Learned Movements Depends upon the Somatosensory Cortex in Humans
Bibliographic record
Abstract
Studies using magnetic brain stimulation indicate the involvement of somatosensory regions in the acquisition and retention of newly learned movements. Recent work found an impairment in motor memory when retention was tested shortly after the application of continuous theta-burst stimulation (cTBS) to the primary somatosensory cortex, compared with stimulation of the primary motor cortex or a control zone. This finding that the somatosensory cortex is involved in motor memory retention whereas the motor cortex is not, if confirmed, could alter our understanding of human motor learning. It would indicate that plasticity in sensory systems underlies newly learned movements, which is different than the commonly held view that adaptation learning involves updates to a motor controller. Here we test this idea. Participants were trained in a visuomotor adaptation task, with visual feedback gradually shifted. Following adaptation, cTBS was applied either to M1, S1, or an occipital cortex control area. Participants were tested for retention 24 h later. It was observed that S1 stimulation led to reduced retention of prior learning, compared with stimulation of M1 or the control area (with no significant difference between M1 and control). In a further control, cTBS was applied to S1 following training with unrotated feedback, in which no learning occurred. This had no effect on movement in the retention test indicating the effects of S1 stimulation on movement are learning specific. The findings are consistent with the S1 participation in the encoding of learning-related changes to movements and in the retention of human motor memory.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".