Visual learning in social insects: From simple associations to higher-order problem solving

Abstract

Visual learning allows the acquisition of new environmental information, which in turn allows adaptive responses when viewing already experienced events again. This capacity is crucial in contexts such as search for food, partner recognition, navigation and defense against potential enemies. It admits different levels of complexity, from simple associative link formation between a visual stimulus (e. g. a specific color) and the consequence of it (e. g. reward or punishment), to more sophisticated performances such as categorization of objects (e. g. animal vs. non-animal) or apprehending abstract rules applicable to unknown visual objects (e. g. “larger than” or “on top of”). In principle, mastering categories and rules allows flexible responses beyond simple forms of learning. Not surprisingly, higherorder forms of visual learning have been mainly studied in vertebrates with larger brains, while the study of simple visual learning has been restricted to animals with small brains such as insects. However, this dichotomy has recently changed, as research on visual learning in social insects (mainly bees and wasps) has yielded surprising results in terms of the sophistication of the tasks that can be mastered. In parallel, the accessibility and small size of insect brains have allowed the characterization of some neural mechanisms of visual learning. Here I review a spectrum of visual learning forms in social insects, from color and pattern learning, visual attention, and top-down image recognition to inter-individual recognition, conditional discrimination, category learning and rule extraction. I discuss the necessity and sufficiency of simple associations to account for complex visual learning and profit from the extensive knowledge on brain organization in insects to discuss neural mechanisms underlying these visual performances.