IntelliCage Analysis Toolkit Example Dataset

This archive contains a fully synthetic IntelliCage-style example dataset generated for the ic-analysis Python toolkit. It is intended for documentation, tutorials, software testing, and reproducible workflow demonstrations. The dataset mimics a realistic group-based place-learning/place-reversal experiment with two simulated 10-mouse groups. It includes IntelliCage-like raw export tables for visits and nose pokes, subject-resolved licking information, metadata, manifests, and generated result files. The implanted synthetic phenotype includes stronger saccharin engagement, faster place learning, and better reversal performance in Group A, compared with weaker saccharin engagement, slower or incomplete learning, and stronger perseveration in Group B. The dataset was deliberately generated with realistic timing complications: Group B starts as a separate cage run 12 days after Group A and shows a 7.5 h delay before the first phase-1 visit events. This makes the archive useful for testing whether analysis workflows correctly align biological phase windows across staggered cage runs instead of relying on absolute timestamps or export-folder names. The dataset is synthetic and does not contain real animal data. It should be used as a benchmark, tutorial, and validation resource for ic-analysis, not as evidence for a biological phenotype. Generated with: additional_scripts/generate_synthetic_group_ab_data.pyExample analysis workflow: user_scripts/place_learning_example.pySoftware repository: https://github.com/FabrizioMusacchio/ic-analysis