Abstract
Motion in the visual periphery of lizards, and other animals, often causes a shift of visual attention toward the moving object. This behavioral response must be more responsive to relevant motion (predators, prey, conspecifics) than to irrelevant motion (windblown vegetation). Early stages of visual motion detection rely on simple local circuits known as elementary motion detectors (EMDs). We presented a computer model consisting of a grid of correlation-type EMDs, with videos of natural motion patterns, including prey, predators and windblown vegetation. We systematically varied the model parameters and quantified the relative response to the different classes of motion. We carried out behavioral experiments with the lizard Anolis sagrei and determined that their visual response could be modeled with a grid of correlation-type EMDs with a spacing parameter of 0.3° visual angle, and a time constant of 0.1 s. The model with these parameters gave substantially stronger responses to relevant motion patterns than to windblown vegetation under equivalent conditions. However, the model is sensitive to local contrast and viewer-object distance. Therefore, additional neural processing is probably required for the visual system to reliably distinguish relevant from irrelevant motion under a full range of natural conditions.
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Abbreviations
- EMD:
-
Elementary motion detector
- 2DMD:
-
Two-dimensional motion detector
- SD:
-
Standard deviation
References
Borst A, Egelhaaf M (1989) Principles of visual motion detection. Trends Neurosci 12:297–306
Borst A, Egelhaaf M (1993) Detecting visual motion: theory and models. In: Miles FA, Wallman J (eds) Visual motion and its role in the stabilisation of gaze. Elsevier, Amsterdam
Dror RO, O’ Carroll DC, Laughlin SB (2001) Accuracy of velocity estimation by Reichardt correlators. J Opt Soc Am A 18:241–252
Dukas R (2002) Behavioral and ecological consequences of limited attention. Phil Trans R Soc Lond B 357:1539–1547
Eckert MP, Zeil J (2001) Towards an ecology of motion vision. In: Zanker JM, Zeil J (eds) Motion vision: computational, neural and ecological constraints. Springer, Berlin
Ewert J-P (1984) Tectal mechanisms that underlie prey-catching and avoidance behavior in toads. In: Vanegas H (ed) Comparative neurology of the optic tectum. Plenum, New York
Fleishman LJ (1986) Motion detection in the presence and absence of background motion in an Anolis Lizard. J Comp Physiol A 159:711–720
Fleishman LJ (1988) Sensory influences on physical design of a visual display. Anim Behav 36:1420–1424
Fleishman LJ (1992) The influence of the sensory system and the environment on motion patterns in the visual displays of anoline lizards and other vertebrates. Am Nat 139:S36–S61
Fleishman LJ, Persons M (2001) The influence of stimulus and background colour on signal visibility in the lizard Anolis cristatellus. J Exp Biol 204:1559–1575
Fleishman LJ, Marshall CJ, Hertz PE (1995) Comparative study of temporal response properties of the visual system of three species of anoline lizards. Copeia 1995:422–431
Hailman JP (1977) Optical signals. Indiana U Press, Bloomington
Hammet ST, Thompson PG, Bedingham S (2000) The dynamics of velocity adaptation in human vision. Curr Biol 10:1123–1126
Ibbotson MR, Clifford CWG (2001) Characterizing temporal delay filters in biological motion detectors. Vision Res 41:2311–2323
Ingle DJ (1982) Organization of visuomotor behaviors in vertebrates. In: Ingle DJ, Goodale MA, Mansfiedl RJW (eds) Analysis of visual behavior. MIT Press, Cambridge
Land MF (1999) Motion and vision: why animals move their eyes. J Comp Physiol A 185:341–352
Meso AI, Zanker JM (2009) Speed encoding in correlation motion detectors as a consequence of spatial structure. Biol Cybern 100:361–370
Nalbach H-O (1989) Three temporal frequency channels constitute the dynamics of the optokinetic system of the crab. Carcinus maenas (L.). Biol Cybern 61:59–70
Ord T, Stamps JA (2008) Alert signals enhance animal communication in “noisy” environments. Proc Natl Acad Sci USA 105:18830–18835
Ord T, Peters R, Clucas B, Stamps JA (2007) Lizards speed up visual displays in noisy motion habitats. Proc R Soc Lond B 274:1057–1062
Persons MH, Fleishman LJ, Frye MA, Stimphil ME (1999) Sensory response patterns and the evolution of visual signal design in anoline lizards. J Comp Physiol A 184:585–607
Peters R (2008) Evironmental motion delays the detection of movement-based signals. Biol Lett 4:2–5
Peters RA, Evans CS (2003) Design of the jacky dragon visual display: signal and noise characteristics in a complex moving environment. J Comp Physiol A189:447–459
Peters RA, Clifford CWG, Evans CS (2002) Measuring the structure of dynamic visual signals. Anim Behav 64:131–146
Peters R, Hemmi J, Zeil J (2007) Signalling against the wind: modifying motion signal structure in response to increased noise. Curr Biol 17:1231–1234
Peters R, Hemmi J, Zeil J (2008) Image motion environments: background noise for movement-based animal signals. J Comp Physiol A 194:441–456
Pough FH (1991) Recommendations for the care of amphibians and reptiles in academic institutions. ILAR J Suppl 33:1–21
Reichardt W (1961) Autocorrelation, a principle for the evaluation of sensory information by the central nervous system. In: Rosenblith WA (ed) Principles of Sensory Communication. Wiley, New York, pp 303–317
Rosenthal GG (2007) Spatiotemporal dimensions of visual signals in animal communication. Annu Rev Ecol Evol Syst 38:155–178
Roth G (1987) Visual behavior in salamanders. Springer, Berlin
Straw AD (2003) Neural responses to moving natural scenes. Ph.D. Thesis. University of Adelaide, Adelaide
Straw AD, Rainsford T, O’Carroll DC (2008) Contrast sensitivity of insect motion detectors to natural images. J Vis 8:1–9
Zanker JM, Zeil J (2005) Movement-induced motion signal distributions in outdoor scenes. Netw Comp Neural 16:357–376
Zeil J, Zanker JM (1997) A glimpse into crabworld. Vision Res 37:3417–3426
Zeil J, Boeddeker N, Hemmi JM (2008) Vision and organization of behaviour. Curr Biol 18:R321–R323
Acknowledgments
We thank Jochen Zeil for introducing us to two-dimensional EMD modeling of natural scenes, and for helpful comments on the manuscript. Johannes Zanker provided us with a version of his 2DMD model, and suggested improvements for our implementation of the model. Michael Rudko assisted with the theory and MATLAB programming. We thank M. Leal and one anonymous reviewer for suggested improvements on an earlier draft of the manuscript. This work was supported by a grant to Union College from the Howard Hughes Medical Institute. The early phases of this study were supported by a visiting scientist fellowship to LJF (hosted by J. Zeil) from the Centre for Visual Sciences at The Australian National University. We followed the Recommendations for the Care of Amphibians and Reptiles (Pough 1991) in treatment of animals used in this study. Animal usage was approved by the Union College Institutional Animal Care and Use Committee (protocol no. 1064). The experiments comply with the “Principles of animal care”, publication No. 86–23, revised 1985 of the National Institute of Health, and also with the current laws of the US.
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Pallus, A.C., Fleishman, L.J. & Castonguay, P.M. Modeling and measuring the visual detection of ecologically relevant motion by an Anolis lizard. J Comp Physiol A 196, 1–13 (2010). https://doi.org/10.1007/s00359-009-0487-7
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DOI: https://doi.org/10.1007/s00359-009-0487-7