- KOREAN
- P-ISSN2287-8327
- E-ISSN2288-1220
- SCOPUS, KCI
ISSN : 2287-8327
Integration of Optimality, Neural Networks, and Physiology for Field Studies of the Evolution of Visually-elicited Escape Behaviors of Orthoptera: A Minireview and Prospects
Piotr Grzegorz Jablonski
Abstract
Sensing the approach of a predator is critical to the survival of prey, especially when the preyhas no choice but to escape at a precisely timed moment. Escape behavior has been approached from both proximate and ultimate perspectives. On the proximate level, empirical research about electrophysiological me-chanisms for detecting predators has focused on vision, an important modality that helps prey to sense approa-ching danger. Studies of looming-sensitive neurons in locusts are a good example of how the selective sensitivity of nervous systems towards specific targets, especially approaching objects, has been understood and realis-tically modeled in software and robotic systems. On the ultimate level, general optimality models have provided an evolutionary framework by considering costs and benefits of visually elicited escape responses. A recent pa-per showed how neural network models can be used to understand the evolution of visually mediated antipre-datory behaviors. We discuss this new trend towards integration of these relatively disparate approaches, the proximate and the ultimate perspectives, for understanding of the evolution of behavior of predators and prey. Focusing on one of the best-studied escape pathway models, the Orthopteran LGMD/DCMD pathway, we discus how ultimate-level optimality modeling can be integrated with proximate-level studies of escape behaviors in animals.
- keywords
- Antipredatory behavior, Escape, Locusts, Movement detecting neurons, Neural networks, Optimality model
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