Development of motor maps in rats and their modulation by experience
Bibliographic record
Abstract
While a substantial literature demonstrates the effect of differential experience on development of mammalian sensory cortices and plasticity of adult motor cortex, characterization of differential experience on the functional development of motor cortex is meager. We first determined when forelimb movement representations (motor maps) could be detected in rats during postnatal development and then whether their motor map expression could be altered with rearing in an enriched environment consisting of group housing and novel toys or skilled learning by training on the single pellet reaching task. All offspring had high-resolution intracortical microstimulation (ICMS)-derived motor maps using methodologies previously optimized for the adult rat. First, cortical GABA-mediated inhibition was depressed by bicuculline infusion directly into layer V of motor cortex and ICMS-responsive points were first reliably detected on postnatal day (PND) 13. Without relying on bicuculline disinhibition of cortex, motor maps emerged on PND 35 and then increased in size until PND 60 and had progressively lower movement thresholds. Second, environmental enrichment did not affect initial detection of responsive points and motor maps in non-bicuculline-treated pups on PND 35. However, motor maps were larger on PND 45 in enriched rat pups relative to pups in the standard housing condition. Rats in both conditions had similar map sizes on PNDs 60, 75, and 90. Third, reach training in rat pups resulted in an internal reorganization of the map in the hemisphere contralateral, but not ipsilateral, to the trained forelimb. The map reorganization was expressed as proportionately more distal (digit and wrist) representations on PND 45. Our data indicate that both environmental enrichment and skilled reach training experience can differentially modify expression of motor maps during development.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".