Opening the “black box” of modeling animal color vision: a comment on Olsson et al.

Opening the “black box” of modeling animal color vision: a comment on Olsson et al. 284 Behavioral Ecology Osorio D, Vorobyev M. 1996. Colour vision as an adaptation to frugivory in RNL model is widely used to describe large perceptual distances primates. Proceedings of the Royal Society B. 263:593–599. in color space. Scholtyssek C, Osorio DC, Baddeley RJ. 2016. Color generalization across In terms of discriminating colors from a very similar back- hue and saturation in chicks. Journal of Vision. 8:1–10 ground (camouflage), receptor noise is unlikely to be the limiting Sterling P, Laughlin S. 2015. Principles of neural design. Cambridge MA: MIT Press. factor determining discrimination thresholds in many ecologi- Vorobyev M. 1997. Discrimination of natural colours and receptor spec- cally relevant conditions. Some of the factors influencing real - tral sensitivity functions. In: Tadei-Ferretti C, editor. Biophysics of pho- ized thresholds mentioned by Olsson et al. (2018) include the toreception: molecular and phototransductive events. Singapore: World costs of making perceptual errors, phenotypic plasticity and Scientific. p. 263–272 learning in color discrimination, the illumination intensity of Vorobyev M, Brandt R, Peitsch D, Laughlin SB, Menzel R. 2001. Colour thresholds and receptor noise: behaviour and physiology compared. the background, and spatial frequency and noise within the Vision Res. 41:639–653. visual scene. Vorobyev M, Osorio D. 1998. Receptor noise as a determinant In terms of supra-threshold differences, many questions in of colour thresholds. Proceedings of the Royal Society B. 265: behavioral ecology concern highly conspicuous signals that are 351–358. very different from the background to which the eyes are adapted. As Olsson et  al. (2018) highlight, under these conditions, detec- tion thresholds are likely to be larger than predicted by the Weber- Fechner law of proportional processing (Akre and Johnsen 2014). Opening the “black box” of modeling The empirical observation that variability of ornamental traits animal color vision: a comment on Olsson increases with increasing conspicuousness could be because detec- et al. tion thresholds increase with increasing conspicuousness—they are not fixed ( Delhey et al. 2017). Devi Stuart-Fox Olsson et al.’s (2018) review compiles estimates of receptor noise School of BioSciences, The University of Melbourne, Parkville, from the vision science literature, which is not easily accessible to Victoria, 3010, Australia behavioral ecologists. It also opens the “black box” of modeling animal color vision by clearly explaining assumptions and limita- What do animals see? This question is central to all behavioral and tions. Both will pave the way for a more judicious use of the RNL ecological interactions involving the transfer of visual information. model by behavioral ecologists. Ultimately though, behavioral ecol- We cannot imagine what an animal sees; but we can attempt to ogists will be the ones testing hypotheses regarding color perception model it. The most widely used mathematical model of animal in ecologically relevant conditions. color vision is the “Receptor Noise Limited” (RNL) model pro- posed by Vorobyev and Osorio 20 years ago (Vorobyev and Osorio 1998). It can be applied to any animal because it is based on a Address correspondence to D. Stuart-Fox. E-mail: d.stuart-fox@unimelb.edu.au relatively small number of parameters and low-level visual physiol- Received 20 October 2017; editorial decision 24 October 2017; accepted ogy, making no assumptions about higher-level processing. But here 27 October 2017; Advance Access publication 22 November 2017. lies the rub because, as highlighted by Olsson et al.’s (2018) review, doi:10.1093/beheco/arx154 many other factors influence how colors are ultimately perceived. The key take-home message of this review is that visual models Editor-in-Chief: Leigh Simmons generate hypotheses about color perception; but these hypotheses need to be validated with behavioral data because perception is REFERENCES often context-dependent. The RNL model was originally formulated to describe detec- Akre KL, Johnsen S. 2014. Psychophysics and the evolution of behavior. tion thresholds—the smallest differences that can be perceived Trends Ecol Evol. 29:291–300. Delhey K, Szecsenyi B, Nakagawa S, Peters A. 2017. Conspicuous plumage under ideal viewing conditions. The RNL model shows a good fit colours are highly variable. Proc Roy Soc Lond B. 284:20162593. to the limited behavioral data on detection thresholds in a variety Olsson P, Lind O, Kelber A. 2018. Chromatic and achromatic vision: of taxa but other models may provide an equally good or better fit, parameter choice and limitations for reliable model predictions. Behav depending on the species and conditions (Renoult et al. 2017). If Ecol. 29:273–282. receptor noise is the limiting factor determining detection thresh- Renoult JP, Kelber A, Schaefer HM. 2017. Colour spaces in ecology and evolutionary biology. Biol Rev Camb Philos Soc. 92:292–315. olds, how good are our estimates of receptor noise? The estimates Vorobyev M, Osorio D. 1998. Receptor noise as a determinant of colour compiled by Olsson et al. (2018) show sometimes large variation thresholds. Proc Biol Sci. 265:351–358. within and between species. This suggests that other factors, such as the motivation of the animals and experimental conditions, are likely to influence estimates of receptor noise. Consequently, RNL Receptor noise models: time to consider model predictions, even based on the best available estimates of alternatives?: a comment on receptor noise, need to be treated as reasonable hypotheses at best. Olsson et al. Behavioral ecologists are generally not concerned with estimates of receptor noise. Instead, there are two relevant issues to behav- Trevor Price and Kristina Fialko ioral ecologists, depending on the question being addressed. First, Department of Ecology and Evolution, 1101 E 57th Street, University how well does the RNL model describe detection thresholds in of Chicago, IL 60637 USA nature? Detection thresholds are critical to many ecological and evolutionary questions, for example, regarding camouflage. Second, how well does the RNL model describe supra-threshold differ - Behavioral experiments are crucial to understand animal vision. ences? Although formulated to describe detection thresholds, the A  common experiment is to assess the just noticeable difference Downloaded from https://academic.oup.com/beheco/article-abstract/29/2/284/4652272 by Ed 'DeepDyve' Gillespie user on 16 March 2018 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Behavioral Ecology Oxford University Press

Opening the “black box” of modeling animal color vision: a comment on Olsson et al.

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Abstract

284 Behavioral Ecology Osorio D, Vorobyev M. 1996. Colour vision as an adaptation to frugivory in RNL model is widely used to describe large perceptual distances primates. Proceedings of the Royal Society B. 263:593–599. in color space. Scholtyssek C, Osorio DC, Baddeley RJ. 2016. Color generalization across In terms of discriminating colors from a very similar back- hue and saturation in chicks. Journal of Vision. 8:1–10 ground (camouflage), receptor noise is unlikely to be the limiting Sterling P, Laughlin S. 2015. Principles of neural design. Cambridge MA: MIT Press. factor determining discrimination thresholds in many ecologi- Vorobyev M. 1997. Discrimination of natural colours and receptor spec- cally relevant conditions. Some of the factors influencing real - tral sensitivity functions. In: Tadei-Ferretti C, editor. Biophysics of pho- ized thresholds mentioned by Olsson et al. (2018) include the toreception: molecular and phototransductive events. Singapore: World costs of making perceptual errors, phenotypic plasticity and Scientific. p. 263–272 learning in color discrimination, the illumination intensity of Vorobyev M, Brandt R, Peitsch D, Laughlin SB, Menzel R. 2001. Colour thresholds and receptor noise: behaviour and physiology compared. the background, and spatial frequency and noise within the Vision Res. 41:639–653. visual scene. Vorobyev M, Osorio D. 1998. Receptor noise as a determinant In terms of supra-threshold differences, many questions in of colour thresholds. Proceedings of the Royal Society B. 265: behavioral ecology concern highly conspicuous signals that are 351–358. very different from the background to which the eyes are adapted. As Olsson et  al. (2018) highlight, under these conditions, detec- tion thresholds are likely to be larger than predicted by the Weber- Fechner law of proportional processing (Akre and Johnsen 2014). Opening the “black box” of modeling The empirical observation that variability of ornamental traits animal color vision: a comment on Olsson increases with increasing conspicuousness could be because detec- et al. tion thresholds increase with increasing conspicuousness—they are not fixed ( Delhey et al. 2017). Devi Stuart-Fox Olsson et al.’s (2018) review compiles estimates of receptor noise School of BioSciences, The University of Melbourne, Parkville, from the vision science literature, which is not easily accessible to Victoria, 3010, Australia behavioral ecologists. It also opens the “black box” of modeling animal color vision by clearly explaining assumptions and limita- What do animals see? This question is central to all behavioral and tions. Both will pave the way for a more judicious use of the RNL ecological interactions involving the transfer of visual information. model by behavioral ecologists. Ultimately though, behavioral ecol- We cannot imagine what an animal sees; but we can attempt to ogists will be the ones testing hypotheses regarding color perception model it. The most widely used mathematical model of animal in ecologically relevant conditions. color vision is the “Receptor Noise Limited” (RNL) model pro- posed by Vorobyev and Osorio 20 years ago (Vorobyev and Osorio 1998). It can be applied to any animal because it is based on a Address correspondence to D. Stuart-Fox. E-mail: d.stuart-fox@unimelb.edu.au relatively small number of parameters and low-level visual physiol- Received 20 October 2017; editorial decision 24 October 2017; accepted ogy, making no assumptions about higher-level processing. But here 27 October 2017; Advance Access publication 22 November 2017. lies the rub because, as highlighted by Olsson et al.’s (2018) review, doi:10.1093/beheco/arx154 many other factors influence how colors are ultimately perceived. The key take-home message of this review is that visual models Editor-in-Chief: Leigh Simmons generate hypotheses about color perception; but these hypotheses need to be validated with behavioral data because perception is REFERENCES often context-dependent. The RNL model was originally formulated to describe detec- Akre KL, Johnsen S. 2014. Psychophysics and the evolution of behavior. tion thresholds—the smallest differences that can be perceived Trends Ecol Evol. 29:291–300. Delhey K, Szecsenyi B, Nakagawa S, Peters A. 2017. Conspicuous plumage under ideal viewing conditions. The RNL model shows a good fit colours are highly variable. Proc Roy Soc Lond B. 284:20162593. to the limited behavioral data on detection thresholds in a variety Olsson P, Lind O, Kelber A. 2018. Chromatic and achromatic vision: of taxa but other models may provide an equally good or better fit, parameter choice and limitations for reliable model predictions. Behav depending on the species and conditions (Renoult et al. 2017). If Ecol. 29:273–282. receptor noise is the limiting factor determining detection thresh- Renoult JP, Kelber A, Schaefer HM. 2017. Colour spaces in ecology and evolutionary biology. Biol Rev Camb Philos Soc. 92:292–315. olds, how good are our estimates of receptor noise? The estimates Vorobyev M, Osorio D. 1998. Receptor noise as a determinant of colour compiled by Olsson et al. (2018) show sometimes large variation thresholds. Proc Biol Sci. 265:351–358. within and between species. This suggests that other factors, such as the motivation of the animals and experimental conditions, are likely to influence estimates of receptor noise. Consequently, RNL Receptor noise models: time to consider model predictions, even based on the best available estimates of alternatives?: a comment on receptor noise, need to be treated as reasonable hypotheses at best. Olsson et al. Behavioral ecologists are generally not concerned with estimates of receptor noise. Instead, there are two relevant issues to behav- Trevor Price and Kristina Fialko ioral ecologists, depending on the question being addressed. First, Department of Ecology and Evolution, 1101 E 57th Street, University how well does the RNL model describe detection thresholds in of Chicago, IL 60637 USA nature? Detection thresholds are critical to many ecological and evolutionary questions, for example, regarding camouflage. Second, how well does the RNL model describe supra-threshold differ - Behavioral experiments are crucial to understand animal vision. ences? Although formulated to describe detection thresholds, the A  common experiment is to assess the just noticeable difference Downloaded from https://academic.oup.com/beheco/article-abstract/29/2/284/4652272 by Ed 'DeepDyve' Gillespie user on 16 March 2018

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Behavioral EcologyOxford University Press

Published: Mar 1, 2018

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