Honeybee Visual Search Strategies Across Training and Test Phases

Linde Morawetz provides four datasets on Apis mellifera (honeybee) decision-making during visual search for vertical targets. The data capture correct and false decisions, decision times, and flight angles across treatment groups and learning blocks. The datasets are divided into training and test phases, with measurements segmented by target position and distance from the entrance.

Use Cases

• Modeling learning curves based on correct and false decision counts across training blocks.
• Analyzing decision time differences between treatment groups (dorsal, ventral, mixed) during test phases.
• Studying flight path angles in relation to target position and distance from the hive entrance.
• Comparing error rates for targets placed in top versus bottom rows across different learning stages.

Strengths

• Contains four distinct datasets covering training decisions, test phase metrics, and flight angles.
• Data is structured by treatment groups (dorsal, ventral, mixed) and learning blocks, allowing for controlled comparisons.
• Flight angle data includes measurements at specific distance segments (e.g., 0-5 cm, 5-10 cm) from the entrance.

Limitations

• Row count and overall dataset size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred from the description after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Linde Morawetz via paperswithcode

Collection Method

Likely collected from controlled laboratory experiments with filmed honeybees.