- Apply for Authority
- 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
- Downloaded
- Viewed
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
Reference
Beddington JR, Free CA, Lawton JH. 1975. Dynamic complexity in predator-prey models framed in difference equations. Nature 255: 58-60.
Berryman A. 1992. The origins and evolution of predator-prey theory. Ecology 73: 1530-1535.
Blanchard M, Rind FC, Verschurea PFMJ. 2000. Collision avoidance using a model of the locust LGMD neuron. Robot Auton Syst 30: 17-38.
Blumstein DT. 2003. Flight-initiation distance in birds is dependent on intruder starting distance. J Wildl Manag 67: 852-857.
Blumstein DT, Botton A, DaVeiga J. 2006. How does the presence of predators influence the persistence of antipredator behavior? J Theor Biol 239: 460-468.
Broom M, Ruxton GD. 2005. You can run-or you can hide: Optimal strategies for cryptic prey. Behav Ecol 16: 534-540.
Burrows M. 1996. The Neurobiology of an Insect Brain. Oxford University Press, New York.
Burrows M, Rowell CHF. 1973. Connections between descending visual interneurons and metathoracic motoneurons in the locust. J Comp Physiol 85: 221-234.
Cooper Jr. WE. 2006. Risk factors and escape strategy in the grasshopper Dissosteira carolina. Behaviour 143: 1201-1218.
Cooper Jr. WE, Frederick WG. 2007. Optimal flight initiation distance. J Theor Biol 244: 59-67.
Dumont JPC, Robertson M. 1986. Neuronal circuits: An evolutionary perspective. Science 233: 849-853.
Fouad K, Libersat F, Rathmayer W. 1996. Neuromodulation of the escape behavior of the cockroach Periplaneta americana by the venom of the parasitic wasp Ampulex compressa. J Comp Physiol A 178: 91-100.
Fullard HF, Yack JY. 1993. The evolutionary biology of insect hearing. Trends Ecol Evol 8: 248-252.
Gabbiani F, Krapp HG, Koch C, Laurent G. 2002. Multiplicative computation in a visual neuron sensitive to looming. Nature 420: 320-324.
Gabbiani F, Laurent G, Hatsopoulos N, Krapp HG. 1999. The many ways of building collision-sensitive neurons. Trends Neurosci 22: 437-438.
Gahtan E, Sankrithi N, Campos JB, O'Malley DM. 2002. Evidence for a widespread brain stem escape network in larval zebrafish. J Neurophysiol 87: 608-614.
Gray JR. 2005. Habituated visual neurons in locusts remain sensitive to novel looming objects. J Exp Biol 208: 2515-2532.
Hale ME, Long Jr. JH, McHenry MJ, Westneat MW. 2002. Evolution of behavior and neural control of the fast-start escape response. Evolution 56: 993-1007.
Hatsopoulos N, Gabbiani F, Laurent G. 1995. Elementary computation of object approach by a wide-field visual neuron. Science 270: 1000-1003.
Holmqvist MH, Srinivasan MV. 1991. A visually evoked escape response of the housefly. J Comp Physiol A 169: 451-459.
Jabłoński PG, Strausfeld N. 2000. Exploitation of an ancient escape circuit by an avian predator: prey sensitivity to model predator display in the field. Brain Behav Evol 56: 94-106.
Konish M. 1986. Centrally synthesized maps of sensory space. Trends Neurosci 9: 163-168.
Magnhagen C. 1991. Predation risk as a cost of reproduction. Trends Ecol Evol 6: 183-186.
Marler P. 1991. Song-learning behavior: The interface with neuroethology. Trends Neurosci 14: 199-205.
Medan V, Oliva D, Tomsic D. 2007. Characterization of lobula giant neurons responsive to visual stimuli that elicit escape behaviors in the Crab Chasmagnathus. J Neurophysiol 98: 2414-2428.
Oliva D, Medan V, Tomsic D. 2007. Escape behavior and neuronal responses to looming stimuli in the crab Chasmagnathus granulatus (Decapoda: Grapsidae). J Exp Biol 210: 865-880.
O’Shea M, Rowell CHF. 1976. The neuronal basis of a sensory analyzer, the acridid movement detector system. J Exp Biol 65: 289-308.
O’Shea M, Williams JLD. 1974. The anatomy and output connections of a locust visual interneurone: the lobular giant movement detector (LGMD) neurone. J Comp Physiol 91: 257-266.
Rind FC, Bramwell DI. 1996. Neural network based on the input organization of an identified neuron signaling impending collision. J Neurophysiol 75: 967-985.
Rind FC, Santer RD. 2004. Collision avoidance and a looming sensitive neuron: Size matters but biggest is not necessarily best. Proc R Soc Lond B 271: S27-S29.
Rind FC, Simmons PJ. 1992. Orthopteran DCMD neuron: A reevaluation of responses to moving objects. I. Selective responses to approaching objects. J Neurophysiol 68: 1654-1666.
Rind FC, Simmons PJ. 1999. Seeing what is coming: building collision-sensitive neurons. Trends Neurosci 22: 215-220.
Rowell CHF. 1971. The orthopteran descending movement detector (DMD) neurones: a characterisation and review. 2. Vgl Physiol 73: 167-194.
Santer RD, Simmons PJ, Rind FC. 2005. Gliding behaviour elicited by lateral looming stimuli in flying locusts. J Comp Physiol A 191: 61-73.
Shepherd GM. 1988. Neurobiology. Oxford University Press, New York.
Simmons PJ, Rind FC. 1992. Orthopteran DCMD neuron: a reevaluation of responses to moving objects. II. Critical cues for detecting approaching objects. J Neurophysiol 68: 1667-1682.
Stafford R, Santer RD, Rind FC. 2007. A bio-inspired visual collision detection mechanism for cars: Combining insect inspired neurons to create a robust system. Biosystems 87: 164-171.
Stafford R, Santer RD, Rind FC. 2007. The role of behavioural ecology in the design of bio-inspired technology. Anim Behav 74: 1813-1819.
Trimarchi JR, Schneiderman AM. 1993. Giant fiber activation of an intrinsic muscle in the mesothoracic leg of Drosophila melanogaster. J Exp Biol 177: 149-167.
Wu JC, Popović Z. 2003. Realistic modeling of bird flight animations. In Proceedings of SIGGRAPH. 2003: 888-895.
Ydenberg RC, Dill LM. 1986. The economics of fleeing from predators. Adv Study Behav 16: 229-249.
Yoshida T, Jones LE, Ellner SP, Fussmann GF, Hairston Jr. NG. 2003. Rapid evolution drives ecological dynamics in a predator–prey system. Nature 424: 303-306.
Zucker RS. 1972. Crayfish escape behavior and central synapses. I. Neural circuit exciting lateral giant fiber. J Neurophysiol 35: 599-620.
- Downloaded
- Viewed
- 0KCI Citations
- 0WOS Citations