Honeybee antennal positioning data when following dances

Antennal positioning data of nestmates following waggle dances included in the publication Hadjitofi and Webb (2024), doi: https://doi.org/10.1016/j.cub.2024.02.045.SummaryThe honeybee waggle dance has been widely studied as a communication system, yet we know little about how nestmates assimilate the information needed to navigate towards the signaled resource. They are required to detect the dancer's orientation relative to gravity and duration of the waggle phase and translate this into a flight vector with a direction relative to the sun1 and distance from the hive2;3. This dataset provides the positions of nestmates and their antennae when following dances obtained from high-speed, high-resolution video recordings of Apis mellifera within the hive. Our work4 uncovered a previously unremarked correlation between antennal position and the relative body axes of dancer and follower bees. We also showed how a neural circuit5;6 first proposed to underlie path integration could be adapted to use this antennal input to decode the dance. We include the performance of the model in this dataset too.CodeThe code used to compute features of the antennae data ("antennae_data") as well as simulate and analyse the results of the assimilation circuit ("model_results") is available at: https://github.com/annahadji/dance2vec.DataThere are two types of files available in this dataset (which can be used to reproduce the published figures):Antennae data:Antennal positioning is given in two main formats (reflected in the naming of the csvs): features (antennal features for each labelled bee in each frame) and binned (antennal features computed over bins of angles to the dancer).Features given (using signed angles) per frame / bin: dancer's angle relative to gravity, nestmate's angle to gravity, angle of nestmate relative to dancer, angle of left antenna, angle of right antenna, angle of midpoint between antennae and angle between the antennae scapes ('s-s' angle).Antennal features are given either using the full length of the antennae (full_antenna_len) or the angle between the base to halfway point or bend (mid_antenna_len) or default (uses full antennae length if available and halfway point as fallback).The values of Batchelet's straightness index of bees' angles to the dancer when treated as a path over time.Model results: Each file represents the results of simulating the model in a particular configuration when using real nestmates' antennal positioning data as input. Configuration parameters: feature of antennal position used (information from both antennae; midpoint of antennae; left antenna; right antenna; or gravity heading only), maximum antennal angle before clipping (90; or 60 degrees), and the number of bins to use for binning angles to the dancer (4; or 24). The results of each configuration may then be given in three formats: errors (error for each bee at each time point), reduced_errors (mean for each bee computed over all time points) and binned_errors (mean error computed across bins of angles to dancer).The performance of the model is measured as the error of the assimilated foodward flight vectors relative to the mean waggle phase angle of the dancer for the time followed. A positive error angle indicates that the assimilated vector is deviated to the left of the target angle and a negative error indicates it deviates to the right.Referencesv. Frisch, K. (1949). Die Polarisation des Himmelslichtes als orientierender Faktor bei den Tänzen der Bienen. Experientia, 5(4), 142-148.Srinivasan, M. V., Zhang, S. W., Lehrer, M., & Collett, T. S. (1996). Honeybee navigation en route to the goal: visual flight control and odometry. Journal of Experimental Biology, 199(1), 237-244.Esch, H. E., Zhang, S., Srinivasan, M. V., & Tautz, J. (2001). Honeybee dances communicate distances measured by optic flow. Nature, 411(6837), 581-583.Hadjitofi, A. & Webb, B. (2024). Dynamic antennal positioning allows honeybee followers to decode the dance. Current Biology, https://doi.org/10.1016/j.cub.2024.02.045.Lyu, C., Abbott, L. F., & Maimon, G. (2022). Building an allocentric travelling direction signal via vector computation. Nature, 601(7891), 92-97.Lu, J., Behbahani, A. H., Hamburg, L., Westeinde, E. A., Dawson, P. M., Lyu, C., ... & Wilson, R. I. (2022). Transforming representations of movement from body-to world-centric space. Nature, 601(7891), 98-104.