Multibehavioral Phenotyping in Larval Zebrafish for Neurotoxicity Screening

A 2.0 MB dataset from figshare published by David Leuthold on June 2, 2026, under a CC-BY-NC-4.0 license. It contains results from a battery of automated behavioral assays in larval zebrafish designed to screen chemicals for neurotoxicity. The study specifically focuses on identifying compounds that disrupt nonassociative habituation learning and uses orthogonal validation with mouse neurons and human stem cell-derived models.

Use Cases

• Training ML models to classify neuroactive chemicals based on behavioral patterns described in the study.
• Identifying chemical compounds that affect nonassociative learning, as referenced in the dataset's objective.
• Correlating in silico target predictions with observed behavioral alterations in zebrafish.
• Benchmarking new neurotoxicity screening methods against the multibehavioral phenotyping approach described.

Strengths

• Data is associated with a published experimental methodology using automated behavioral assays.
• Includes orthogonal validation from mouse cortical neurons and human 3D BrainSpheres, as described in the results.
• Dataset is shared under a specific, permissive license (CC-BY-NC-4.0).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

David Leuthold via figshare

Collection Method

Data likely originates from automated behavioral assays on larval zebrafish, pharmacological interventions, and ex vivo validation as described.

Freshness

Last updated 2026-06-02 13:37:14; freshness should be verified.