Enrichment-induced forgetting is associated with white matter microstructure in mice
Bibliographic record
Abstract
Memories are stored in brain circuits, sometimes referred to as engrams. Forgetting happens when these neural activity patterns fail to be reactivated by retrieval cues. Neuroplasticity can destabilize existing memory circuits by altering the fidelity of neural signals and contribute to forgetting. Existing research has described plasticity in grey matter that contributes to forgetting; however, plasticity within white matter has not been explored. Here, brain plasticity was induced after contextual fear conditioning by housing mice in environmentally-enriched multilevel cages (EE) for four weeks. EE mice demonstrated forgetting as measured by reduced time spent freezing during the fear conditioning test compared to mice housed in standard cages (SE) (EE<SE β=-52.2%, p=1.1×10 -11 ). Ex vivo brain diffusion-weighted MRI was used to assess enrichment-induced plasticity in white matter and revealed that fractional anisotropy (FA) was increased in the anterior commissure, cerebral peduncle, corpus callosum, cortical spinal tract, and fimbria, in EE mice compared to SE mice (10% FDR). In EE mice, increased FA in the corpus callosum and fimbria predicted reduced freezing (p<0.05), suggesting that in these tracts, white matter changes induced by enrichment may contribute to forgetting. Consistent with the above, administering clemastine fumarate, a pro-myelinating drug, induced forgetting in male mice (β=-23.5%, p=0.009). Neurogenesis, an established mechanism that contributes to forgetting, indexed by the volume of the granule cell layer of the dentate gyrus, independently predicted forgetting (β=-13.6%, p=0.036). These findings indicate that myelin-related plasticity in white matter tracts that support contextual fear memory may play a role in enrichment-induced forgetting. • Environmental enrichment leads to forgetting of a contextual fear memory • Environmental enrichment is associated with changes in white matter microstructure • White matter microstructure and neurogenesis indexed with MRI are independently associated with forgetting
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".