Animal behaviour though a virtual lens: an innovative approach to quantifying motion signals and motion noise (#106)
To appreciate fully the forces that shape the behaviour of animals, it is necessary to understand the information-processing tasks under evolution relevant conditions. Knowledge of the environment in which animals operate and the sensory processing demands that mediate behaviour are crucial. Motion vision plays crucial roles in the life of animals. Although much is known about the computational and neural principles of motion vision, information on the conditions for motion vision in natural environments is limited. Important insights into the sensory and ecological limitations that govern behaviour have been gained from studying animal signals, and indeed the use of movement to communicate is widespread in the animal kingdom, including our own attempts to attract the attention of others by waving our arms (and our efforts to enhance this signal in crowded places). The diversity we see in signal structure directly reflects ecological factors. Equally important are the sensory and cognitive abilities of receivers that ultimately constrain signal structure. Detailed descriptions of signal structure must go hand-in-hand with careful analysis of the structure and dynamics of environmental noise within which those signals must function. Two fundamental questions arise: How are natural, biologically relevant motion stimuli distinguished from extraneous motion noise? What are the sensory limitations that necessitate a change in signalling behaviour? Using Australia’s Agamid lizards as a model system we are developing an innovative approach that combines novel fieldwork techniques with 3D modeling technologies to determine how habitat characteristics, weather and motion vision influences signalling behaviour.