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Record W4408724683 · doi:10.1002/cne.70043

Environmental Enrichment Increases Brain Volume in Snakes

2025· article· en· W4408724683 on OpenAlexafffund
Gokulan Nagabaskaran, Vijay Moonilal, Morgan Skinner, Noam Miller

Bibliographic record

VenueThe Journal of Comparative Neurology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsWilfrid Laurier University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyCaptivityEnvironmental enrichmentBrain sizeZoologyOphidiaEcologyNeuroscience

Abstract

fetched live from OpenAlex

The effects of environmental enrichment have been well documented in mammals and birds, but less work has focused on reptiles. Because snakes are common in captivity, both as pets and in research/commercial facilities, it is critical to explore how they react to standard captive housing. Here, we examined the effects of environmental enrichment on brain development in a popular pet snake species, the western hognose snake (Heterodon nasicus). Hognose snakes (n = 15) were individually housed for one year in either enriched or standard environments before their brains were harvested and imaged using MRI. We found that enriched snakes had significantly larger brain volumes compared to standard snakes, most prominently in posterior brain regions. In addition, we observed sex-specific brain investments: as snakes grew larger, males displayed relatively larger cerebral hemispheres, and females displayed larger posterior brain regions. These results suggest that environmental enrichment is critical to encouraging healthy brain development in snakes and that snake brain plasticity is very similar to that observed in mammals and birds.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.011
GPT teacher head0.251
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes2
Has abstractyes

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