title: The answer is blowing in the wind: free-flying honeybees can integrate visual and mechano-sensory inputs for making complex foraging decisions.
abstract: Bees navigate in complex environments using visual, olfactory and mechano-sensorial cues. In the lowest region of the atmosphere, the wind environment can be highly unsteady and bees employ fine motor-skills to enhance flight control. Recent work reveals sophisticated multi-modal processing of visual and olfactory channels by the bee brain to enhance foraging efficiency, but it currently remains unclear whether wind-induced mechano-sensory inputs are also integrated with visual information to facilitate decision making. Individual honeybees were trained in a linear flight arena with appetitive-aversive differential conditioning to use a context-setting cue of 3 m s-1cross-wind direction to enable decisions about either a 'blue' or 'yellow' star stimulus being the correct alternative. Colour stimuli properties were mapped in bee-specific opponent-colour spaces to validate saliency, and to thus enable rapid reverse learning. Bees were able to integrate mechano-sensory and visual information to facilitate decisions that were significantly different to chance expectation after 35 learning trials. An independent group of bees were trained to find a single rewarding colour that was unrelated to the wind direction. In these trials, wind was not used as a context-setting cue and served only as a potential distracter in identifying the relevant rewarding visual stimuli. Comparison between respective groups shows that bees can learn to integrate visual and mechano-sensory information in a non-elemental fashion, revealing an unsuspected level of sensory processing in honeybees, and adding to the growing body of knowledge on the capacity of insect brains to use multi-modal sensory inputs in mediating foraging behaviour.
authors: RMIT University, School of Aerospace, Mechanical and Manufacturing Engineering, Bundoora, VIC 3083, Australia sridhar.ravi@rmit.edu.au.
authors: Sridhar
authors: 0000-0001-7397-9713
authors: S
authors: Ravi
authors: RMIT University, School of Media and Communication, Melbourne, VIC 3000, Australia.
authors: Jair E
authors: JE
authors: Garcia
authors: RMIT University, School of Aerospace, Mechanical and Manufacturing Engineering, Bundoora, VIC 3083, Australia.
authors: Chun
authors: C
authors: Wang
authors: RMIT University, School of Media and Communication, Melbourne, VIC 3000, Australia.
authors: Adrian G
authors: AG
authors: Dyer
mesh_terms: D000818:Animals; D001516:Bees / Q000502:physiology*; D003657:Decision Making; D005247:Feeding Behavior / Q000502:physiology*; D005426:Flight, Animal / Q000502:physiology*; D007858:Learning; D010781:Photography / Q000295:instrumentation; D012201:Reward; D014796:Visual Perception / Q000502:physiology*
keywords: Apis mellifera; Multi-modal processing; Reverse learning; Sensory processing; Vision