Analysis of Antennal Responses to Motion Stimuli in the Honey Bee by Automated Tracking Using DeepLabCut

J Insect Behav (2023) 36:332–346 https://doi.org/10.1007/s10905-023-09845-4 RESEARCH Analysis of Antennal Responses to Motion Stimuli in the Honey Bee by Automated Tracking Using DeepLabCut Hiroki Kohno · Shuichi Kamata · Takeo Kubo Received: 2 November 2023 / Revised: 15 December 2023 / Accepted: 18 December 2023 / Published online: 3 January 2024 © The Author(s) 2024 Abstract Considering recent developments in gene manipulation methods for honey bees, establishing simple and robust assay systems which can analyze behavioral components in detail inside a laboratory is important for the rise of behavioral genetics in the honey bee. We focused on the antennal movements of the honey bee and developed an experimental system for analyzing the antennal responses (ARs) of the honey bee using DeepLabCut, a markerless posture-tracking tool using deep learning. The tracking of antennal movements using DeepLabCut during the presentation of vertical (downward and upward) motion stimuli successfully detected the directionspecific ARs in the transverse plane, which has been reported in the previous studies where bees tilted their antennae in the direction opposite to the motion stimuli. In addition, we found that honey bees also exhibited direction-specific ARs in the coronal plane in response to horizontal (forward and backward) motion stimuli. Furthermore, an investigation of the developmental maturation of honey bee ARs showed that ARs to motion stimuli were not detected in bees Supplementary Information The online version contains supplementary material available at https://doi. org/10.1007/s10905-023-09845-4. H. Kohno (*) · S. Kamata · T. Kubo Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Bunkyo‑ku, Tokyo 113‑0033, Japan e-mail: Vol:. (1234567890) 13 immediately after emergence but became detectable through post-emergence development in an experience-independent manner. Finally, unsupervised clustering analysis using multidimensional data created by processing tracking data using DeepLabCut classified antennal movements into different clusters, suggesting that data-driven behavioral classification can apply to AR paradigms. In summary, our results revealed direction-specific ARs even in the coronal plane to horizontal motion stimuli and developmental maturation of ARs for the first time, and suggest the efficacy of data-driven analysis for behavioral classification in behavioral studies of the honey bee. Keywords Honey bee · Automated tracking · DeepLabCut · Antennal response · Unsupervised behavioral clustering Introduction Genome sequencing and comprehensive gene expression analyses have been conducted on many insect species (Ellegren 2014; Oppenheim et al. 2015). Combined with the establishment of gene manipulation methods (Mello and Conte 2004; Adli 2018), the molecular and neural bases of insect behavior have been elucidated in various non-model insect species other than Drosophila (Sun et al. 2017; Mansourian et al. 2019; Walton et al. 2020). The European honey bee (Apis mellifera) is a well-known social insect, and J Insect Behav (2023) 36:332–346 its social behavior has been extensively studied for many years (Frisch et al. 1967; Winston 1987; Seeley 1995). In addition, genome editing and transgenic technologies have been established and applied for molecular- and neuro-ethological analyses in honey bees (Schulte et al. 2014; Kohno et al. 2016; Otte et al. 2018; Kohno and Kubo 2018, 2019; Roth et al. 2019; Carcaud et al. 2023), although the molecular and neural bases underlying honey bee behaviors still remain to be solved. Most innate behaviors of honey bees, such as nursing their brood, division of labor of workers, and waggle dance, have been described by observations and behavioral experiments in the field (Frisch et al. 1967; Seeley 1995), but genetically modified honey bees must be confined to laboratory conditions due to legal restrictions. To date, a simple and robust behavioral experimental paradigm, olfactory conditioning of the proboscis extension reflex (PER), has been extensively utilized to analyze the abilities and mechanisms of learning and memory of honey bees inside a laboratory (Kuwabara 1957; Giurfa and Sandoz 2012; Eisenhardt 2014). Some previous studies have developed original devices for analyzing bee behaviors and sophisticated psychological experimental paradigms (Giurfa et al. 2001; Kirkerud et al. 2013, 2017; Schultheiss et al. 2017; Howard et al. 2018, 2019; Marchal et al. 2019; Nouvian and Galizia 2019; Geng et al. 2022), but they have not necessarily been widely used due to their uniqueness or difficulties requiring skilled handling of bees with care. Against this background, developing a variety of robust (highly reproducible), simple, and versatile behavioral experimental systems which can be used inside a laboratory other than the olfactory PER associative learning paradigm is important for the rise of honey bee behavioral genetics. We focused on the antennal response (AR) of honey bees as one of these behavioral experimental systems. Insect antennae are essential for various sensory receptions such as olfaction, gustation, and mechanoreception and are used to sense the external world (Vogt and Riddiford 1981; Staudacher et al. 2005; Hallem et al. 2006). Various insect species move their antennae in response to odorants, visual stimuli, and mechanical stimuli (Honegger 1981; Staudacher et al. 2005; Mamiya et al. 2011; Natesan et al. 2019). In honey bees, ARs to motion, odor, and mechanical stimuli and learning-dependent changes 333 in AR to odors have been reported (Suzuki 1975; Erber et al. 1993; Erber and Kloppenburg 1995; Cholé et al. 2015; Gascue et al. 2022). In addition, antennal contact is essential in maintaining society through nestmate recognition and pheromone reception in eusocial insects, including honey bees (Ozaki et al. 2005; Sharma et al. 2015; Gomez Ramirez et al. 2023). To date, multi-animal tracking studies in eusocial insects using individual identification tags have revealed developmental changes in the social behaviors and responses of individuals to different social circumstances, which were inferred from individual positions inside the nest and inter-individual interactions (Mersch et al. 2013; Crall et al. 2015, 2018; Wario et al. 2015; Ai et al. 2017; Stroeymeyt et al. 2018; Liberti et al. 2022). However, by colony-level observations, determining which behavioral components change and affect individual responses is generally difficult. Therefore, the measurement and analysis of antennal movements in honey bees is expected to lead to a better understanding of the behavioral components that influence not only environmental recognition but also social behaviors. In previous studies, the movements of insect antennae were measured by manually determining their position and angle for each frame of video or using phototransistors, which register the movement of t (...truncated)