Do housing-induced changes in brain activity cause stereotypic behaviours in laboratory mice?
Bibliographic record
Abstract
Abnormal repetitive stereotypic behaviours (SBs) (e.g. pacing, body-rocking) are common in animals with poor welfare (e.g. socially isolated/in barren housing). But how (or even whether) poor housing alters animals' brains to induce SBs remains uncertain. To date, there is little evidence for environmental effects on the brain that also correlate with individual SB performance. Using female mice from two strains (SB-prone DBA/2s; SB-resistant C57/BL/6s), displaying two forms of SB (route-tracing; bar-mouthing), we investigated how housing (conventional laboratory conditions vs. well-resourced 'enriched' cages) affects long-term neuronal activity as assessed via cytochrome oxidase histochemistry in 13 regions of interest (across cortex, striatum, basal ganglia and thalamus). Conventional housing reduced activity in the cortex and striatum. However, DBA mice had no cortical or striatal differences from C57 mice (just greater basal ganglia output activity, independent of housing). Neural correlates for individual levels of bar-mouthing (positive correlations in the substantia nigra and thalamus) were also independent of housing; while route-tracing levels had no clear neural correlates at all. Thus conventional laboratory housing can suppress cortico-striatal activity, but such changes are unrelated to SB (since not mirrored by congruent individual and strain differences). Furthermore, the neural correlates of SB at individual and strain levels seem to reflect underlying predispositions, not housing-mediated changes. To aid further work, hypothesis-generating model fit analyses highlighted this unexplained housing effect, and also suggested several regions of interest across cortex, striatum, thalamus and substantia nigra for future investigation (ideally with improved power to reduce risks of Type II error).
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".