Understanding and Reconstruction of the Mobiligence of Insects Employing Multiscale Biological Approaches and Robotics

Abstract

Adaptability, i.e., the ability to behave in accordance with a ceaselessly changing environment, is a defining feature of animals, including insects, and is a necessary attribute in robotics. Insects display a range of sophisticated behaviors in response to their environments based on the processing of a simple nervous system. Insects are uniquely suited for multidisciplinary studies of the brain involving a combined approach at several levels, from molecules and single neurons to neural networks and behavior. Furthermore, insects can be adapted for use with a wide variety of methodological approaches, from molecular genetics, electrophysiology and imaging to computational tools and robotics. Thus, insects are an excellent model taxon for understanding adaptive control in biological systems. In this review, the general features of the insect brain and multiscale approaches for understanding the neural basis of their behavior are introduced. As an example of adaptive behavior in insects, odor–source orientation behavior in silkmoths and the feasibility of a behavioral strategy based on their neural system, with implementation in robots, is described. Finally, we present novel approaches using an insect–machine hybrid, which will enhance our ability to evaluate and understand adaptive behavior.