Meeting Abstract
There is an increasing interest in understanding the neural bases of cognition. Insects, with their miniature nervous systems and their complex behavior, offer a unique opportunity to investigate the interplay between neuronal structures and behavior. Among them, the honeybee Apis mellifera has an incredibly rich behavior and relatively simplified neuroanatomy making it a model for neuroethological studies, including those in high-order learning. For example, after training, free-flying honeybees can categorize, count and extract abstract rules applicable to unknown objects (e.g. “larger than”, “on top of”, “different from”). However, a current gap in visual learning has been the inability to link functional studies on the neural substrates and information processing areas in the brain directly with behavior. Here, we use a locomotion compensator and a visual display to present stimuli to a tethered bee, thus enabling sensorimotor control and neurobiological experimentation in a fixed preparation. Online trajectory information from the locomotion compensator can be send to the visual display and allow the stimuli to move accordingly to the honeybee movement (e.g., close loop). My preliminary results demonstrate that honeybees on the locomotion compensator discriminate visual stimuli with performances that can be compared to free flying honeybees. By coupling this system with multichannel recordings from the optic lobe and mushroom bodies, our aim is to compare neural signatures of different brain structures during and after simple or high-order learning.
