Environmental enrichment accelerates the stabilization of cortical representation during de novo learning
Bibliographic record
Abstract
Environmental enrichment is an established strategy to enhance learning and to build resilience against neurodegeneration. This work aimed to study the functional encoding dynamics of cortical neurons in enriched mice performing a virtual spatial foraging task. Thy1-GCaMP6s mice were enriched by running a complex obstacle course, with different types of hurdles requiring climbing, jumping, and/or balancing elements. Two-photon calcium imaging was conducted on populations of neurons from the secondary motor cortex before, during, and after repeated locomotion through a virtual environment with visual-tactile cues. We observed an increase in memory reactivation during the first day of exposure. With training, enriched animals exhibited a stronger anticipatory response near the reward location. Moreover, cortical neurons became substantially more stable over days. Altogether, these results indicate that prior environmental enrichment accelerates the stabilization of cortical activity during learning and enables faster and more robust acquisition of new sequence representations of a novel task.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".