Animal colour vision - behavioural tests and physiological concepts

Kelber, Almut; Vorobyev, Misha; Osorio, Daniel

Published in: Biological Reviews

DOI: 10.1017/S1464793102005985

2003

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Citation for published version (APA): Kelber, A., Vorobyev, M., & Osorio, D. (2003). Animal colour vision - behavioural tests and physiological concepts. Biological Reviews, 78(1), 81-118. https://doi.org/10.1017/S1464793102005985

Total number of authors: 3

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LUND UNIVERSITY

PO Box 117 221 00 Lund +46 46-222 00 00 Biol. Rev. (2003), 78, pp. 81–118 " Cambridge Philosophical Society 81 DOI: 10.1017\S1464793102005985 Printed in the United Kingdom Animal colour vision – behavioural tests and physiological concepts

ALMUT KELBER"*, MISHA VOROBYEV#† and DANIEL OSORIO$ " Department of Cell and Organism Biology, Vision Group, Lund University, HelgonavaW gen 3, S-22362 Lund, Sweden # Department of Biological Sciences, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA $ School of Biological Sciences, University of Sussex, Falmer, Brighton BN1 9QG, UK

(Received 3 September 2001; revised 15 April 2002)

ABSTRACT

Over a century ago workers such as J. Lubbock and K. von Frisch developed behavioural criteria for establishing that non-human animals see colour. Many animals in most phyla have since then been shown to have colour vision. Colour is used for specific behaviours, such as phototaxis and object recognition, while other behaviours such as motion detection are colour blind. Having established the existence of colour vision, research focussed on the question of how many spectral types of photoreceptors are involved. Recently, data on photoreceptor spectral sensitivities have been combined with behavioural experiments and physiological models to study systematically the next logical question: ‘what neural interactions underlie colour vision?’ This review gives an overview of the methods used to study animal colour vision, and discusses how quantitative modelling can suggest how photoreceptor signals are combined and compared to allow for the discrimination of biologically relevant stimuli.

Key words: colour, vision, model, behaviour, photoreceptor, threshold.

CONTENTS

I. Introduction ...... 82 II. Photoreceptor signals ...... 83 (1) Diversity of receptors...... 83 (2) Spectral tuning of receptors...... 86 (a) Measurement of receptor sensitivities...... 86 (b) Visual pigments ...... 86 (c) Filters ...... 87 (3) Modelling receptor signals...... 87 III. Colour vision concepts ...... 88 (1) What is colour vision? ...... 88 (2) Colour spaces, and the number of receptor types used for colour vision...... 89 (3) Achromatic and chromatic signals ...... 89 IV. Uses of chromatic signals ...... 91 V. Tests of colour vision...... 100 (1) Evidence for colour vision ...... 100 (a) Grey card experiments...... 100 (b) Monochromatic stimuli ...... 101 (c) Broadband stimuli at different intensities ...... 102

* Author for correspondence: e-mail: almut.kelber!cob.lu.se † Present address: Vision Touch and Hearing Research Centre, University of Queensland, Brisbane, Queensland, 4072, Australia. 82 Almut Kelber, Misha Vorobyev and Daniel Osorio

(2) Tests of visual mechanisms ...... 102 (a) Colour matching...... 102 (b) Discrimination of specially adjusted stimuli...... 103 (c) Receptor-based models of colour choices ...... 103 VI. Modelling thresholds for colour discrimination...... 103 (1) Measuring thresholds ...... 104 (2) Interpretations of the shapes of threshold sensitivity curves...... 104 (3) Metric spaces and quantitative analysis of threshold data...... 105 (a) Inferring neural mechanisms from threshold data ...... 106 (b) Receptor noise and colour thresholds ...... 108 (4) Threshold models as a tool to study the biological relevance of colour vision...... 109 VII. Conclusions...... 109 VIII. Acknowledgements ...... 109 IX. Appendix A: Colour spaces ...... 109 X. Appendix B: Receptor-noise-limited colour opponent model...... 111 XI. References...... 112

I. INTRODUCTION mechanisms of colour discrimination, such as chro- matic opponency? Human colour science and psychophysics became Concepts in colour vision are mostly derived from established during the nineteenth century, and human perception and psychophysics. Human tri- people began to ask whether animals see colour. chromacy was proposed first in the eighteenth Lubbock (1888) in his book On the senses, instincts and century (Mollon, 1997), and models relating our intelligence of animals demonstrated to his satisfaction colour discrimination to underlying receptor re- that Daphnia sp. see colour, using the fact that they sponses and neural mechanisms are over a century are both positively phototactic, and prefer yellow to old (Maxwell, 1860; Hering, 1878; Helmholtz, white light which is more intense across the entire 1896). When human cone spectral sensitivities were spectrum (see Section V.1c). Lubbock (1888) also first directly measured (Bowmaker & Dartnall, made a good case that honeybees (Apis mellifera) can 1980), they closely matched psychophysical predic- associate colour with food, but did not rule out their tions (Smith & Pokorny, 1975). As animals are more using brightness. It was left to von Frisch (1914) to difficult to test than humans, most work has aimed confirm honeybee colour vision. At the same time simply to establish the existence of colour vision, the problem of equating human colour sensations rather than to determine receptor inputs and neural with animal behaviour was well recognized. One mechanisms. critic (Anonymous, 1889) of Lubbock’s book When Jacobs (1981) wrote his book Comparative doubted that one can conclude that animals taste, Color Vision most studies that went beyond dem- see or hear simply because their movement is direc- onstrating the existence of colour vision were from ted by sense organs analogous to our own. To this mammals, although there was also important work day doubts persist as to whether animals enjoy the on honeybees (Daumer, 1956; von Helversen, 1972). sensation of, and hence can truly be said to see, Work on non-mammalian species is now becoming colour (Cogan, 1995; Stoerig, 1998). Nonetheless, easier thanks to increasing numbers of measurements given the behavioural criteria of Lubbock and von of photoreceptor spectral sensitivities (Table 1). The Frisch (see Section III.1) it is evident that many history of human colour vision can be reversed; once animals use colour for tasks such as phototaxis where spectral inputs to the receptors are known (Fig. 1, spectral composition identifies a light source, and for stage 1) it is possible to study neural processing of detecting and discriminating objects (Menzel, 1979; signals arising from a single stimulus (Fig. 1, stage 2), Jacobs, 1981; Mollon, 1989). and the mechanisms comparing signals from dif- This review deals with three main questions, ferent stimuli (Fig. 1, stage 3). much as suggested by Menzel (1979): (1) Is colour We review two types of tests of colour discrimi- vision used for a particular task? (2) How many nation. Firstly, tests of the ability to make a spectral types of photoreceptor are involved? (3) discrimination (Section V), and secondly measure- What can be said about the post-receptoral neural ments of discrimination thresholds (Section VI). Animal colour vision 83

Before looking at experimental data we outline the vertebrate cone opsin have been recognized (His- diversity of visual photoreceptors that underlie atomi et al., 1994; Bowmaker & Hunt, 1999), it colour vision (Section II), introduce some ideas seems desirable to use the terms VS (‘very short’), S, relevant to understanding colour and how it is M and L to refer to the opsin gene family, and to studied (Section III), and discuss the roles of specify the spectral sensitivity maximum of the achromatic and chromatic signals (Section IV). photopigment (see also Bowmaker & Hunt, 1999). For invertebrate photopigments we simply specify the spectral sensitivity maxima of each species’ visual II. PHOTORECEPTOR SIGNALS pigments or photoreceptors (Table 1). Of invertebrates, Octopus vulgaris like most other (1) Diversity of receptors cephalopod molluscs has a single spectral type of Knowing photoreceptor spectral sensitivities simpli- receptor. Some spiders and crustaceans have two fies the study of colour vision, and phylogenetic types. Daphnia magna and perhaps jumping spiders comparisons give insight into its evolutionary origins (Salticidae) have four, while stomatopod crustaceans and function. For example, haplorrhine primates have up to 16. Among insects, cockroaches (Blatto- (i.e. monkeys and apes) often have three spectral dea) and some ants have two spectral receptor types, types of cone, compared to two in most other while most bees and wasps have three (Peitsch et al., mammals. Perhaps then trichromacy is an adap- 1992). Dragonflies (Odonata) and sawflies (Tenthri- tation to the primates’ particular diurnal lifestyle dinidae) have four spectral types of receptor, and and frugivorous diet (Mollon, 1989). On the other some flies (Diptera) and butterflies have five or more hand, the fact that many bees and wasps have a (Table 1; reviewed by Briscoe & Chittka, 2001). similar set of three photoreceptors to the honeybee In vertebrates, the two main types of visual implies that honeybee trichromacy is not a specific photoreceptor cell, rods and cones, are distinguished adaptation to its being a generalist pollinator, being by a number of morphological and physiological evolutionarily older than the life-style (Peitsch et al., features (Cohen, 1972). Normally, rods are active at 1992). Swallowtail butterflies (Papilio sp.) might low (scotopic) light intensities, and cones at high have evolved a fourth receptor type (sensitive to very (photopic) intensities. Colour vision uses mainly long wavelengths) as an adaptation to oviposition on cone signals, but goldfish (Carassius auratus) may use green leaves rather than to flower detection (Kelber, rods and red (L) cones in dim light (down to 1 or 2 1999). log units above absolute threshold: Powers & Easter, Data on visual pigment and photoreceptor spec- 1978b), and rods contribute to colour vision in tral sensitivities are increasing, especially for verte- amphibians (Muntz, 1963) and humans (Wyszecki brates. Microspectrophotometry (MSP) can be used & Stiles, 1982). where intracellular recording is difficult. Molecular Of the more primitive vertebrates, lampreys have genetics shows how opsins (pigment proteins) have one rod and two anatomically distinct types of cone evolved, and how specific aminoacid residues de- (Collin, Potter & Braekevelt, 1999), but only two termine spectral tuning (Bowmaker, 1998; Bow- photopigments have been described (Table 1). maker & Hunt, 1999; Nathans, 1999). Table 1 Many teleost fishes, reptiles and birds have one rod indicates the range in numbers and spectral tuning and four cone opsins. These form five families of photoreceptors in a selection of molluscs, arthro- defined by amino acid sequences and characterized pods and vertebrates. by the locations of their spectral sensitivity maxima Photoreceptor nomenclature is complicated, and (Table 1; Hisatomi et al., 1994; Bowmaker, 1998; potentially confusing. Receptors have been named Bowmaker & Hunt, 1999): rod, very short (VS, or either according to the part of the spectrum to which violet\ultraviolet), short (S, or blue), medium (M, they are absolutely or relatively most sensitive: or green) and long (L, or red). Rana spp. frogs also ‘red’, ‘green’, ‘blue’, ‘UV’ etc., or by their have up to five receptor types, however two of them sensitivity relative to other receptors in the eye for are rods (a ‘red’ rod and a ‘green’ rod, Table 1). example ‘long’ (L), ‘short’ (S) and ‘medium’ (M) Vertebrate lineages often lose visual photopigments, wavelength sensitive. This nomenclature is satis- for example many teleost fish along with most factory for referring to a given species or closely mammals have only two cone pigments, while related group of species, but is less satisfactory and snakes, crocodiles and geckos have three. potentially confusing for more general comparisons. Mammals lost two cone opsin families, probably Moreover, given that four main gene families of during an early ‘nocturnal’ phase of evolution, 84 Almut Kelber, Misha Vorobyev and Daniel Osorio , the , see Section ( sensitivity maxima , . (1992) . (1998) et al et al We give the species names and do not take account of . , For invertebrates ). . (1999) . (1983) et al . (1994) . (1991) et al . (1991); Palacios . (1993) et al et al . (1987) . (1999) . (1988) et al et al . (1996) long wavelength et al . (1981) ( et al et al et al L et al ger ), $ Koskelainen Reviews: Menzel & Backhaus (1991); Briscoe & Chittka (2001) Cronin & Marshall (1989); Marshall & Oberwinkler (1999) Review: Marshall Bowmaker Kro † † 623 570 † † artificially expressed ) G medium wavelength - ( they are generally sensitivities of isolated receptors ) M MSP ), ( 600 Nosaki (1969) \ mostly intracellular for invertebrates and suction electrode recordings for vertebrates; ERG ? 431 502 562 Liebman & Entine (1968); Govardovsii & Zueva (1974); , (maxima from Vertebrate receptors are classified according to the probable gene family of their opsin other reviews listed give additional information about specific taxa j . , 315 to 654 nm) 502* other than ERG ( short wavelength ( S E 522ERG 356 430 447 537 \ \ ), MSP 12 \ E MSP ) E 360 490 520 580 Yamashita & Tateda (1976) ) MSP 470 485 500 Matsui and sensitivity maxima ) E 360 520 Blest ) E 330 430 490 520 620 Meinertzhagen ) E 506 400 444 610 Perry & McNaughton (1991) ) E 365 510 Mote & Goldsmith (1970) sp., , electrophysiological recording , ) E 340 480 520 Walla whereas for vertebrates ) 460 560 ) MSP 515 555 Govardovskii & Lychakov (1984) )MSP ) E 348 434 525 608 Smith & Macagno (1990) ) E 335 355 460 490 530 Hardie (1986) ) E 470 Messenger (1981) ) MSP 500 453 530 ) MSP 549 465 549 613 Govardovskii ) E 344 436 556 Menzel & Blakers (1976); Peitsch ) E 360 400 440 520 600 Arikawa microspectrophotometry of photoreceptors or , ) E 340 470 520 Hariyama in vivo, including sp.) E 360 490 540 Wilkens (1984) Methods: E Plexippus validus Menemerus confusus Neogonodactylus . Cupiennius salei sp.) Watasenia scintillans ) Ambystoma tigrinum Periplaneta americana Daphnia magna Sympetrum rubicundum spp.* Apis mellifera Musca domestica Lampetra lampetra Acipenser baeri Papilio xuthus Procambarus clarkii Carrassius auratus Octopus vulgaris Tridacna Aequidens pulcher Ligia exotica very short wavelength or UV receptor Examples of receptors in different animal classes ( Rana catesbeiana . Odontodactylus R :VS Cockroach ( Dragonfly ( Isopod ( Crayfish ( Goldfish ( Mantis shrimp ( Honeybee ( Bivalva ( Jumping spider ( Jumping spider ( Water flea ( House fly ( Frog ( Salamander ( Octopus ( Firefly squid ( Ctenid spider ( Sturgeon ( Butterfly ( Lamprey ( Cichlid ( ) intraocular filtering electroretinogram; MSP method used to determine sensitivity Insects Table 1. Animal groupMolluscs Spiders Crustaceans Method Sensitivity maxima (nm) Reference Amphibians* are mostly of receptors Vertebrates Rod VS S M L Reviews: Bowmaker (1995) (fish); Bowmaker (1998) II Animal colour vision 85 . (1987) et al . 1997; Hart 2001 et al . (1997) . (1991) et al . (1998) et al et al Sillman Reviews: Bowmaker Review: Jacobs (1993) Bowmaker & Dartnall (1980); Schnapf † ‡ 564 ‡ E 498 437 533 \ ., 1994; Partridge & Cummins, 1999). Dehydroxyretinal red-shifts the spectral sensitivity by over 50 nm et al ) MSP 501 444 535 566 ) MSP-G 488 524 Fasick ) MSP 500 355 454 499 568 Maier & Bowmaker (1993) ) MSP-G 358 437 495 560 Kawamura & Yokoyama (1998) ) MSP 360 450 518 620 Baylor & Hodgkin (1973); Loew & Govardovskii (2001) sp.) ERG 500 436 518 Jacobs (1993) ) MSP 506 418 455 507 569 Bowmaker ) MSP 364 467 521 Loew (1994) Leiothrix lutea Alligator mississippiensis Gallus gallus Tursiops truncatus Spermophilus Anolis carolinensis Pseudymys scripta Gekko gekko † Bird double cones contain the long-wavelength-sensitive visual pigmentPrimate and M are and not L thought receptor to pigments contribute are to both colour derived vision, from fishes the can mammal use L double pigment. They are named M and L for convenience. Turtle ( Lizard ( Gecko ( Crocodile ( Chicken ( Human MSP Pekin robin ( Dolphin ( Squirrel ( Birds for long-wavelength-sensitive opsins. Where† receptors may use bothcones types for of colour chromophore vision we‡ and give the the pigments value of for the the principle retinal-bearing and variant. accessory cones are given. Reptiles * Some vertebrates includingreceptor various or fish even and a amphibia single express cell both (e.g. retinal Firsov and dehydroxyretinal as the chromophore in a single class of photo- Mammals 86 Almut Kelber, Misha Vorobyev and Daniel Osorio

(2) Spectral tuning of receptors (a) Measurement of receptor sensitivities A photoreceptor’s spectral sensitivity is given by the relative likelihood of absorption of a photon incident on the cornea, as a function of its wavelength. Once a photon is absorbed, the electrical responses of visual photoreceptors are (so far as is known) independent of its wavelength. This ‘principle of univariance’ (Rushton, 1965) means that the inten- sities of two visible spectra can always be adjusted to give equal responses, so that individual photorecep- tors are ‘colour blind’. Spectral sensitivities can be established in various ways (Table 1). In invertebrates, the usual and direct method is by intracellular recording from photoreceptors in vivo the response to (typically) monochromatic stimuli of known intensity (Autrum & von Zwehl, 1964; Peitsch et al., 1992). In vertebrates, suction electrode recording of isolated receptors is often more practical (Schnapf, Kraft & Baylor, 1987). Electroretinograms (ERG) combined with selective adaptation are widely used with Fig. 1. (A) Diagram of a four-stage model of colour vertebrates (Jacobs, 1993), but may be difficult to discrimination by a trichromatic eye (modified from interpret when there are three or more spectral types Brandt & Vorobyev, 1997). Stage 1: responses of receptors of receptor. Alternatively, absorption spectra of (r, rh) sensitive to short (S), medium (M) and long (L) photopigments, and other visual media can be wavelengths of light, to reference and test stimuli. Stage 2: measured by spectrophotometry, and receptor spec- achromatic and\or chromatic interactions between sig- tral sensitivities can be estimated from these spectra. nals. Three mechanisms are needed to represent all the ! ! ! Spectrophotometry can be performed either in information (x", x#, x$, for the reference and x", x#, x$, for photoreceptors (Liebman & Entine, 1968; Cronin & the test stimulus) encoded by three receptor types. Stage et al 3: ∆S represents the distance of the two stimuli in colour Marshall, 1989; Bowmaker ., 1997), or artificial space, this distance depends on the metrics (see Figs 3, 4). expression systems (Asenjo, Rim & Oprian, 1994; At stage 4, either the test or the reference stimulus is Fasick et al., 1998; Nathans, 1999). Finally, spectral selected with a probability Pcorr. (B) Model that does not sensitivity of some vertebrate pigments can now be include stage 2 mechanisms; many models are of this type, predicted from the amino acid composition of the see Figs 3B, C, 4C, and 5A, ii and iii. opsin (Asenjo et al., 1994; Nathans, 1999; Bowmaker & Hunt, 1999). leaving them with L and VS opsins (Jacobs, 1993; Bowmaker, 1998; Bowmaker & Hunt, 1999). Mam- (b) Visual pigments malian VS photopigment and cones are commonly called ‘S’ (i.e. short-wavelength sensitive). This S Visual photopigments are G-protein-coupled recep- cone opsin is probably absent from dolphins and tors, which comprise an opsin protein and a seals (Peichl, Behrmann & Kro$ ger, 2001) and from carotenoid chromophore. When a chromophore nocturnal species including racoons (Procyon spp.) absorbs a photon it isomerizes, and this causes the and owl monkey (Aotus sp.; Ahnelt & Kolb, 2000); opsin to change conformation to activate phototrans- these species are cone monochromats. Conversely, duction (Aidley, 1998). The visual pigment’s spectral many primates, including all known Old-World sensitivity depends both upon the chromophore and monkeys (Catarrhini), have recovered three types of the opsin, but for a given chromophore the shape of cone pigment by evolving separate ‘L’ (red) and the curve is a predictable function of the peak ‘M’ (green) opsins from the ancestral L opsin gene wavelength (Dartnall, 1953; Govardovskii et al., (Bowmaker, 1998; Nathans, 1999). 2000). The commonest chromophore is retinal, the Animal colour vision 87 aldehyde derivative of vitamin A1, but fishes, seems unlikely because, at least in turtles and birds amphibians and reptiles sometimes have 3,4- four types of oil droplets are each associated with a dehydroxyretinal, the derivative of vitamin A2 (por- specific type of single cone photopigment (Bowmaker phyropsin; Wald, 1939; Provencio, Loew & Foster, et al., 1997; Loew & Govardovskii, 2001). Typically, 1992), and many insects use 3-hydroxyretinal, a oil droplets cut off light of short wavelengths from a derivative of xanthophylls (Vogt & Kirschfeld, value around the sensitivity maximum of the opsin 1984). Substitution of A2 for A1 red-shifts sensitivity, (Hart, 2001), and this appreciably sharpens spectral and this underlies some variation in fish and tuning. Model calculations have recently provided amphibians (Liebman & Entine, 1968). The squid clear evidence that this sharpening indeed benefits Watasenia scintillans is remarkable for having three colour vision (Vorobyev et al., 1998). visual pigments based on one opsin and three types In the grasshopper Phaeoba sp., corneal filters over of chromophore (Matsui et al., 1988). Normally a single spectral type of photopigment may indeed though, the main source of variability in spectral provide a basis for colour vision (Kong, Fung & sensitivities is the opsin. For A1-based visual pig- Wasserman, 1980). Corneal filters are common in ments, sensitivity maxima range from approximately tachinid flies, but it is uncertain how they affect 310 nm to 570 nm, and for A2-based pigments up to spectral sensitivities. More generally, invertebrates 635 nm (Provencio et al., 1992). have a wide variety of intraocular filters using Usually a single photoreceptor cell contains one photostable pigments (Douglas & Marshall, 1999). type of visual pigment, but there are exceptions, the Also, some compound eyes such as those of butterflies best known being the presence of mixtures of A1 and and stomatopods have ‘tiered retinae’ where light A2 visual pigments in fish and amphibians (Firsov, passes first through ‘distal’ receptor cells in an Govardovskii & Donner, 1994). Mouse (Mus mus- ommatidium, and so is filtered, before it reaches the culus), and possibly wallaby (Macropus eugenii) ex- proximal cells (Cronin & Marshall, 1989; Douglas press two different opsins in the same cone photo- & Marshall, 1999). In compound eyes, there is also receptor (Ro$ hlich, van Veen & Szel, 1994; Hemmi ‘lateral’ filtering, where several photoreceptor spec- &Gru$ nert, 1999; Neitz & Neitz, 2001). The tral types combine to form a single light-guiding swallowtail butterfly (Papilio xuthus) has a complex rhabdom and hence compete for photons (see set of photoreceptors, some of which co-express two Section II.3). opsin genes (Kitamoto et al., 1998). Other receptors in this butterfly express a single opsin, but adopt different sensitivities depending on the presence of (3) Modelling receptor signals 3-hydroxyretinol, which works as a UV-absorbing The physical stimulus for vision is the number of screening pigment (Arikawa et al., 1999). On the quanta absorbed by a receptor per unit time (e.g. other hand, flies use 3-hydroxyretinol as an antennal receptor integration time). Due to the availability of pigment, which broadens spectral sensitivity by cheaper spectrophotometers large numbers of biolo- adding a UV peak (Hardie, 1986; Vogt, 1989). gically relevant stimuli have recently been measured and used for modelling. Where the spectral dis- (c) Filters tribution of a light stimulus, I(λ) is known, the quantum catch, Q , of a receptor type i, with spectral Receptor sensitivities depend primarily on their i sensitivity, R (λ), is given by: visual pigments, but ocular filters often have a i marked effect (Walls, 1942; Douglas & Marshall, Qi l I(λ) Ri(λ)dλ, (1) 1999). Yellow lenses of diurnal mammals and some & fishes absorb UV and violet light. The coloured oil where integration is over the visible spectrum. droplets in cone inner segments of many diurnal Stimulus intensity can be given either in quantum or reptiles and birds are of particular interest (Walls, in energy units, but the units of light stimulus and 1942; Partridge, 1989; Goldsmith, 1991; Hart, spectral sensitivity must correspond. Quantum units 2001). These droplets vary in colour, and early are commonly used in animal studies, and are workers attributed a variety of functions to them, appropriate since photoreceptors act as quantum most notably as a basis for colour vision in animals counters. In human psychophysics, energy units are assumed to have only a single visual pigment (e.g. more often used. If E(λ) is the spectrum of a light Walls, 1942; King-Smith, 1969). For vertebrates this stimulus in energy units, then the spectrum in latter theory was doubted by Walls (1942), and now quantal units, I(λ), is given by: 88 Almut Kelber, Misha Vorobyev and Daniel Osorio

I(λ) l λ\hc E(λ), (2) those of brightness and saturation, and is the attribute denoted by terms such as red, yellow, green where h is Planck’s constant and c the velocity of or purple (Wyszecki & Stiles, 1982; Byrne & Hilbert, light. Similarly, the relationship of spectral sen- 1997; Backhaus, Kliegl & Werner, 1998). Brightness sitivity in quantum units, Ri(λ), to that in energy E is the achromatic aspect of colour, and hue and units, Ri (λ) is given by: saturation are chromatic aspects. There is no evidence that animals perceive hue, saturation or R (λ) hc\λ RE(λ). (3) i l i brightness as separate qualities, or that they cat- Usually relative rather then absolute sensitivity is egorize colours as yellow, red etc. Indeed some important, in which case the constant hc is omitted, workers insist that colour perception requires con- and spectral sensitivity is transformed from energy to sciousness; what we call colour vision, on be- quantum units by dividing by wavelength. To derive havioural criteria, Stoerig (1998) recognizes as spectral sensitivity from spectrophotometric measure- ‘wavelength information processing’. ments, let Fi(λ) be the attenuation of incoming light A comprehensive definition of colour from the by optical filters in the light path to the visual standard handbook of colour science (Wyszecki & pigments, and ki(λ) the extinction coefficient (ab- Stiles, 1982, p. 487) is ‘that aspect of visual sorption in a thin layer) of a pigment i, and x the perception by which an observer may distinguish length of a photoreceptor. Then the receptor differences between two structure-free fields of view response, Ri(λ), is given by: of the same size and shape, such as may be caused by differences in the spectral composition of the radiant Ri(λ) l CFi (λ)o1kexp[kki(λ)x]q. (4) energy …’. The advantage of this definition is that it is not based on the human sensation of colour but on C is a proportionality factor that describes the a physical measurement – ‘the spectral composition receptor’s absolute sensitivity. The second term in of radiant energy’ – therefore it can be applied to eqn (4) describes ‘self-screening’ by the visual animals. Paradoxically, by this definition, the ability pigment, which being spectrally selective, removes to discriminate colours does not entail colour vision. the wavelengths to which it most sensitive so that the Humans discriminate colours by means of chro- long receptor has a broadened spectral sensitivity. matic (hue, saturation) as well as achromatic Warrant and Nilsson (1998) give a simplified (brightness) signals. Colour-blind people (mono- expression for this term. When x is small chromats, including all humans in very dim light 1kexp(kki(λ)x) % ki(λ)x. For arthropod eyes op- intensities) discriminate many colours by means of tical modelling is complicated, because light may be brightness. Colour vision, in humans, therefore filtered as it travels along the rhabdom (photorecep- means the ability to discriminate colours by their tors). In fused rhabdoms, the visual pigments of chromatic aspect, even though achromatic signals different receptor types act as filters for each other contribute to human colour perception, i.e. subjects thus narrowing the spectral sensitivity of each with colour vision can discriminate colours of equal receptor type. If sensitivities of the pigments are brightness. We do not know whether animals known, spectral sensitivities can be calculated (Sny- perceive brightness or hue, thus a general working der, Menzel & Laughlin, 1973). definition for colour vision needs to be based on a physical criterion. Brightness relates to the sensitivity of the achromatic channel in a visual system. A light of 700 nm wavelength of high intensity might look as III. COLOUR VISION CONCEPTS bright as a light of 550 nm at low intensity. Intensity is measured as the number of quanta incident on the (1) What is colour vision? eye per unit area, angle in space and unit time Understanding colour starts from our own subjective interval. For monochromats, it is always possible to experience. Colours have the qualities of hue, adjust the intensities of two spectral stimuli to yield saturation and brightness. Brightness is the value on equal sensations. For humans with colour vision, the dark to light scale. Saturation describes a colour’s colours with different saturation or hue cannot similarity to a neutral grey or white: a grey object be made indiscriminable by adjusting stimulus with a small reddish tint has low saturation, whereas intensity. a red object with little white or grey tint is highly When describing animal colour vision we will saturated. Hue refers to colour differences other than refer to intensity-related cues as achromatic cues, Animal colour vision 89 and to the signal they generate in the animal’s visual receptors used independently for colour discrimi- system, as the achromatic signal. In humans, this nation (see Section V.2). Colour matching includes signal leads to the perception of brightness. We the possibility that one of the primaries is added conclude that an animal has colour vision if it can negatively – i.e. it is added to the colour that one discriminate two lights of different spectral com- tries to match instead of the other primaries. position, regardless of their relative intensity (e.g. Otherwise it is not possible to match colours that lie DeValois & DeValois, 1997; Menzel, 1979; Neu- outside the polygon in the colour space set by the meyer, 1991; Goldsmith, 1991; Byrne & Hilbert, primaries. 1997). Section V describes experiments required to For humans, spectral sensitivities of the cardinal test colour vision. axes of commonly used colour spaces (e.g. RGB, XYZ; Wyszecki & Stiles, 1982) were chosen before the cone sensitivities were known. Likewise, Daumer (1956) proposed a trichromatic colour space for (2) Colour spaces, and the number of honeybees from colour-matching experiments. But receptor types used for colour vision Daumer’s work is an exception, and in most animal As we have just seen, animals with a single spectral studies the cardinal axes of colour spaces represent type of photoreceptor are monochromats in that it is receptor responses (Appendix 1; Menzel & Back- always possible to adjust the relative intensities of haus, 1991; Neumeyer, 1991; Goldsmith, 1991; two spectra to give identical responses (Rushton, Brandt & Vorobyev, 1997; Vorobyev & Menzel, 1965). If more than one light, or primary, is needed 1999; Osorio, Miklo! si & Gonda, 1999a; Osorio, to match colour the animal has colour vision. Colour Vorobyev & Jones, 1999b). vision is classified as dichromatic, trichromatic, In practice, the dimensionality of colour vision has tetrachromatic etc., according to the number of been studied in few animals. Many mammals are lights required to match any spectral light. This dichromats save primates which are often trichro- number cannot exceed the number of receptor types mats (Jacobs 1981, 1993), as are bees (Daumer, in the eye but may be fewer, and needs to be 1956). Goldfish, turtle (Pseudemys scripta elegans), established behaviourally. Most vertebrates, for pigeon (Columba livia) and chicken (Gallus gallus) are example, normally do not use rods for colour vision. probably tetrachromats (Arnold & Neumeyer, 1987; Flies have two anatomically separate visual path- Neumeyer, 1992; Palacios et al., 1990; Palacios & ways; one of these is probably used for colour vision Varela, 1992; Osorio et al., 1999b). and receives input from four of their five receptor types (Troje, 1993). (3) Achromatic and chromatic signals Normal human observers are trichromats, because any spectrum can be matched by a unique com- The existence of multiple spectral types of photo- bination of three primary spectra. Trichromacy was receptor is not sufficient for colour vision. Sub- first proposed in the eighteenth century by Lomo- sequent neural stages (Fig. 1, stages 2 and 3) are nosov, Palmer and Young (Mollon, 1997), and necessary, and we are generally interested in the established experimentally by Maxwell (1860). The behavioural manifestations of these neural mechan- intensities of the three primaries that match a given isms (Fig. 1, stage 4). In the simplest arrangement, light are called ‘tristimulus values’, and these give a behaviour is directly driven by the response of one or quantitative description of its colour. Tristimulus more receptors to a stimulus (Fig. 1B). When only values are linearly related to the quantum catches in one receptor is involved, behaviour is colour blind, the three types of cone (Fig. 2B; Wyszecki & Stiles, and the corresponding channel is called achromatic. 1982). Hence, for humans colour can be specified When signals of several receptors are directly used to either by the intensities of three known spectra discriminate stimuli behaviour is no longer colour required for a match, or by the quantum catches Qi blind – even if no chromatic interaction occurs. of the three receptor types. A colour can then be Alternatively, receptor signals may interact (Fig. represented geometrically, as a point Q in a colour 1A; stage 2). Visual neurons may either sum space, whose dimensionality is given by the number photoreceptor signals, or compare them by some of primaries required for a colour match, or by the type of inhibitory interaction to give the ratio or number of receptor types involved (Fig. 2, Appendix difference of receptor signals. Chromatic mechan- A). Colour matching establishes directly the dimen- isms involve the comparison of receptor outputs, sionality of colour vision, and thus the number of while achromatic mechanisms involve only additive 90 Almut Kelber, Misha Vorobyev and Daniel Osorio

Fig. 2. Relative sensitivities of photoreceptors (left), receptor spaces (middle), and chromaticity diagrams with mono- chromatic loci (right) for representative di- (A), tri-(B) and tetrachromatic eyes (C). Colour is represented as a point Q in the receptor space, where each co-ordinate axis corresponds to the quantum catches of very short- (VS), short- (S), medium- (M) and long-wavelength-sensitive (L) receptors. Receptor spaces thus have n dimensions for visual systems with n receptors; the four-dimensional receptor space can not be visualized. Chromaticity diagrams (right) where Qi l 1, are projections of the receptor space to nk1 dimensions. A line (dashed) connecting Q with the origin intersects the chromaticity diagram (a line, for dichromats; a plane, for trichromats, and a three-dimensional space, for tetrachromats) in a point qc. The vertices of chromaticity diagrams (VS, S, M, L) represent colours that are represented on the axes of the colour spaces (middle). Colour loci of monochromatic lights are represented by the dashed line, and plotted points every 10 nm (A, B) or 50 nm (C). NP in A indicates the neutral point of a dichromat, i.e. the wavelength of light that has the same chromaticicty coordinates as white light. See Appendix A for details of receptor spaces, and the corresponding chromaticity diagrams. interactions. n degrees of freedom in post-receptoral subsequent models of colour vision implement his neural signals are required to encode all the hypothesis. Hering (1878), on the other hand, information represented by a retina with n spectral argued that interactions are essential, and that two types of photoreceptor. opponent channels – yellow-blue and red-green – Historically, Helmholtz (1896) proposed that underlie human colour sensations. Helmholtz and human colour vision did not require interactions Hering models can be reconciled by recognizing that between the three receptor mechanisms, and many colour vision is a multistage process (Fig. 1; see Animal colour vision 91

Chapter 8 in Wyszecki & Stiles, 1982). Psycho- of photoreceptors across the animal kingdom physical evidence indicates that humans combine (Table 1). their three receptor signals to give one achromatic Despite the lack of a satisfactory quantitative (or luminance) signal, and two chromatic signals model, intuitively it seems reasonable that chromatic (Jameson & Hurvich, 1955; Krauskopf, Williams & signals are useful for object detection and identifi- Heeley, 1982). The achromatic aspect of colour – cation. Under shadows and patchy illumination as in brightness – is mediated by non-opponent mechan- forests or shallow water, variations in light intensity isms, whereas the chromatic aspects of colour – hue cause large variations in receptor signals from a and saturation – are mediated by opponent mech- given surface. The ratio of signals from two receptor anisms. Regardless of whether animals perceive types is however comparatively robust with respect saturation, hue and brightness, we can hypothesize to illumination, and hence a better indicator of that they have similar chromatic and achromatic object properties (Rubin & Richards, 1982; Mollon, mechanisms. Nonetheless, care is required to in- 1989; Maximov, 2000). According to this argument terpret behavioural experiments as evidence for chromatic signals should ideally represent this ratio post-receptoral (stage 2) interactions, and we return of receptor responses, making them insensitive to to this subject in Section VI. variations in intensity, but other signals such as the It should be possible to relate psychophysically differences of receptor responses would also be useful. defined mechanisms to neural responses, but even for Even so, variable illumination will affect chromatic primates this is not easy. Macaque (Macaca macaca) signals, making it necessary to ‘discount’ the retinal ganglion cells, which transmit signals up the illuminant by colour constancy (Hurlbert, 1998). optic nerve, do fall into three main spectral types: Many animals have colour constancy but we do not those coding mainly luminance, yellow-blue op- deal here with this subject, which was reviewed ponent cells, and the cells of the parvocellular recently by Neumeyer (1998). pathway, which probably represent the red-green Given the capacity of nervous systems to combine signal (Dacey, 2000). Ganglion cell spectral sensi- signals with different weightings, and to perform a tivities do not however match psychophysical predic- large variety of operations, the coding of colour tions, for example they fail to predict the redness of should reflect the fact that chromatic and achromatic short wavelength (violet) light. There are recordings signals are useful for different purposes. This means for spectral opponent neurons in many other species, that when achromatic cues are used, as for motion which we cannot review here. However, it is worth detection, chromatic signals are disregarded, and noting that Backhaus (1991) relates electrophysio- when chromatic signals are used, as for the recog- logical recordings from colour opponent neurons in nition of the colour of food sources, achromatic honeybees to opponent mechanisms proposed from information may often be disregarded because it is behavioural studies (see Section V.2c). unreliable. As we have said, one might expect a wide range of animals to have chromatic mechanisms whose responses are independent of intensity. Honeybees are an example of a species with IV. USES OF CHROMATIC SIGNALS intensity-independent colour vision (see Section VI). In his pioneering work, von Frisch (1914) trained Colour vision seems to be useful. Most eyes have bees to feed from a sugar solution presented on a blue multiple spectral types of photoreceptor (Table 1), (or a yellow) card, and found that they could dis- and most animals have colour vision (Table 2), but criminate the training colour from 30 different shades it is not easy to specify the costs and benefits. Costs of grey. Indeed, his bees were unable to learn to arise because colour vision compromises absolute discriminate between greys of different intensity, sensitivity and (often) spatial resolution (van which implied that they had learned only chromatic Hateren, 1993; Osorio, Ruderman & Cronin, 1998). signals. On the other hand, motion vision in honey- Moreover, many processes such as directional mo- bees is colour-blind (Lehrer, 1993). Where animals tion detection are generally colour blind. Various use either chromatic or achromatic cues in different theoretical studies have considered the consequences behaviours, as bees (von Frisch, 1914) and birds of varying the numbers and tuning of spectral (Goldsmith, Collins & Perlman, 1981) do, it can be photoreceptor types (Barlow, 1982; Maloney, 1986; shown very convincingly that an animal discrimi- van Hateren, 1993), but no theory accounts well nates colour stimuli regardless of their relative for the diversity in numbers and spectral tuning intensities. 92 Almut Kelber, Misha Vorobyev and Daniel Osorio we pose , do not provide proof of vision in spiders Porshnyakov (1969); Menzel (1979) screening pigments Reviews: Mazokhin- As in the Introduction . per se ? How many chromatic mechanisms We note whether colour vision has ) . q2 ( Under method we give the type of . Yes First clear evidence for colour Yes Yes very short wavelength receptor; S short wavelength We refer to other review articles for some animal , . VS ( spectral sensitivity curves , used for colour vision is given if it was determined by behavioural ) . (1996) Yes this is mentioned in the comment to one of the questions are listed here For example , . ) . (1980) Ind. Eye bands with different et al stage 2 , et al is involved (2000) & Kuppelwieser (1913) (1998) Fig. 1 ( McEnroe & Dronka (1966)Dimmock & Davids (1985) Ind. Nakamura Yes & Yamashita Koller (1927)Koller (1928)Hyatt (1975) Ind. Koehler (1924), Storz Yes & Paul Marshall Yes Moericke (1950) Yes ) ? How many spectral types of receptor are involved for colour vision ) .) q1 ( ind ( or at least an indication ( receptoral mechanisms that have been shown to use colour vision in different behavioural experiments - long wavelength receptor ) Some experiments gave evidence that a specific receptor see Sections V and VI , , ). phototaxis phototaxis avoidance reaction camouflage phototaxis phototaxis spontaneous choices of shell homes training oviposition Monochromatic stimuli, Monochromatic stimuli, Grey card experiment, heat Grey card experiment, Monochromatic stimuli, Grey card experiment, Grey card experiment, food q2 and q3 ( ) Monochromatic stimuli, ) Broadband stimuli, phototaxis Lubbock (1888), von Frisch excluding primates ) ) Monochromatic stimuli, ( sp.) Broadband stimuli, phototaxis Kong or there is only a strong indication gurus ) - ) Crangon Hasarius Clibanarius Phaeoba Eupa Uca pugilator is colour vision used for a particual behaviour Unionicola , ? Only experiments which give an answer Daphnia magna , ) The number of receptors and post yes to q1 ) ) . ( the behaviour used to test the animal and whether spontaneous or trained behaviour was used ) q3 ) , Animal species Myzodes persicae ( or model calculations \ For detailed descriptions of methods . Tetranchus urticae Odontodactylus scyllaris ( intermedia adansoni misanthropus ( vulgaris anachoretus Two-spotted spider mite Water mite ( Jumping spider ( Common shrimp ( Hermit crabs ( Fiddler crab ( Water flea ( Mantis shrimp Grasshopper ( Aphid ( receptor; M medium wavelength receptor; L groups experiment tests and colour vision been proved are found three questions Table 2. Animal speciesMites Method Reference q1 q2 q3 Comments Spiders Crustaceans Insects Animal colour vision 93 and VI.3) c sensitivity in bees colour instead of grey Vorobyev (1997); Vorobyev & Osorio (1998) model in bees (seeV2. Sections involved used the model by Backhaus (1991) used vision 3 1* *Model calculation & Yes *Use of different shades of ) * *Proof that no L receptor is ) Yes b a . (1999) nique (1999) Yes * *Proof that no L receptor is ! . (1992) Yes* 3 *Model: a modification of et al et al hn (1927) Yes First evidence for UV $ (1969) Lotmar (1933)Mazokhin-Porshnyakov Helversen (1972)Helversen Yes (1972)Backhaus (1991) 3 2* 3 Yes* *Models: Brandt & 3 2 *First colour discrimination Ku Shafir (1996)Beier & Menzel (1972) Yes Yes * *Proof that no L receptor is Wehner & Toggweiler (1972) Yes Knoll (1922)Kelber (1997)Kelber & He Knoll (1926) Yes Schremmer (1941 Ind. Ind.Kelber (1999) Few observations Yes Kelber & Pfaff (1999) Yes * *L receptor used for colour training training training food training (MDS)*, Food training training training training training spontaneous choices, feeding training training training choices, oviposition traning training Grey card experiment, food Grey card experiment*, food Spectral sensitivity, food Wavelength discrimination, Colour mixture, food trainingMultidimensional scaling Daumer (1956) Yes 3 Monochromatic stimuli, food Grey card experiment, food Monochromatic stimuli, food Colour discrimination* Chittka Monochromatic stimuli, Monochromatic stimuli, food Grey card experiment, food Grey card experiment, food Paper colours*, spontaneous Grey card experiment, food Grey card experimentMonochromatic stimuli, food Kinoshita ) ) Grey card experiment, food ) Grey card experiment von Frisch (1914) Yes Hyles Papilio ) Schremmer (1941 Paravespula ) Autographa Cataglyphis Apis mellifera ) ) Vespa rufa ) Polybia occidentalis ) ) Macroglossum stellatarum Papilio xuthus germanica bicolor hymenoptera livornica gamma ( ( aegeus Honeybee ( Wasp ( German wasp ( Hornet ( Desert ant ( Eight species of Hummingbird hawkmoth Striped hawkmoth ( Gamma fly ( Swallowtail butterfly Orchard butterfly ( 94 Almut Kelber, Misha Vorobyev and Daniel Osorio intensity learning ) Yes a ) Yes b tz (1936) Yes . (1975) Yes 2 1* *Model: Kelber 2001 $ et al ffert & Go $ Ilse (1928)Crane (1955)Swihart (1971) Ind. Yes Yes Colour learning but no Scherer & Kolb (1987)Su YesFukushi (1990) 4Troje (1993) 1*Prokopy *Model: Kelber 2001 Ind. Ilse (1949) YesKugler (1950)Lunau & Wacht (1994)von Frisch Yes (1912, Model Yes 1913 proposed Yes 2 1* *Model: Kelber 2001 von Frisch (1913 Wolff (1925) Ind. 4* *Evidence for a VS receptor spontaneous choices, feeding spontaneous choices, feeding training spontaneous choices, feeding and oviposition phototaxis spontaneous choices, feeding spontaneous choices, feeding spontaneous choices, oviposition training spontaneous choices, feeding spontaneous choices, feeding spontanous colour change training food training Grey card experiment, Grey card experiment, Grey card experiment, Wavelength discrimination, Grey card experiment, Monochromatic stimuli, Grey card experiment food Wavelength discrimination, ) Grey card experiment, feeding Knoll (1921) Yes ) Monochromatic stimuli, ) Grey card experiment food ), ) Grey card experiment, ) Grey card experiment, food ) Grey card experiment, ) Grey card experiment, Inachis brassicae ) . P ), brimstone Dacus oleae Argynnis ) Aglais urticae .) Eristalis tenax Phoxinus laevis .) Lucilia cuprina Bombylius fuliginosus cont Heliconius charotonius ), cabbage white cont ), fritillary ( Pieris brassicae Gonepteryx rhamni Aglais urticae io paphia ( peacock butterfly ( ( ( Tortoiseshell ( Heliconius erato Zebra ( Cabbage white ( Tortoiseshell caterpillars Blowfly ( Olive fruit fly ( Bee fly ( Minnow ( Drone fly ( Table 2 ( Animal speciesInsects ( Method Reference q1 q2 q3 Comments Vertebrates Fishes Animal colour vision 95 was measured but taken‘aberrant’ as vision in dim lightrespiration for rate conditioning vision in dim lighttask for the contribute to colour vision for the task under dim light tetrachromatic colour vision in an animal curve are narrower than those of receptor curves Yes )) Ind. 2* Yes 2* *Rod and L cone colour *Rod and L cone colour a b ) Ind. a . (1976) . (1978) . (1975) et al et al et al von Frisch (1913 Powers & Easter (1978 Powers & Easter (1978 Neumeyer & Arnold (1989) Ind.Neumeyer (1984) 3*Neumeyer (1985, 1992)Neumeyer (1985, *Only 1986) VS, S Ind. and Yes M cones 4*Meng Yes* (1958) 4 *FirstGnyubkin direct evidence for Kondrashev Dimentman *Maxima of discrimination Yes Schiemenz (1923)Schiemenz (1923)Beauchamp Yes & Rowe (1977) * Yes Ind. 4* *Indication for a VS receptor *The high sensitivity in UV respiration rate conditioning in dim light respiration rate conditioning in dim light training, dim light training, bright light training food training choice spontaneous colour change dishabituation of turning response training response conditioning, bright light Spectral sensitivity, Monochromatic lights, Spectral sensitivity, food Spectral sensitivity, food Colour matching, food Wavelengh discrimination, Grey card experiment, mate Monochromatic stimuli, food Grey card experiment, escape Grey card experiment Burkamp (1923) Yes ) Spectral sensitivity, heart rate ) Grey card experiment, ) Grey card experiment, ) ), golden Bufo bufo Gasterosteus Carassius auratus ) Crenilabrus melops Tinca tinca Idus melanotus orfe ( aculeatus Common toad ( Wrasse ( Stickleback ( Tench ( Goldfish ( Amphibians 96 Almut Kelber, Misha Vorobyev and Daniel Osorio ) c object detection task used for tests (1982) (see Section V.2 of maxima in sensitivity curve discrimination curve in the sensitivity curve discimination function due to oil droplet absorption Yes . (1995) Ind. 3* *Deduced from the number ger (1985) Ind. 3* *Deduced from four maxima $ . (1999) Ind. et al et al Hailman & Jaeger (1974) Summers Kasperczyk (1971) Yes Himstedt (1972) Yes *Motion vision involved but Przyrembel Falzman & Bastakov (1999)Orlov & Maximov Yes (1982) Yes 3 1* *Model: Losev & Maximov Wojtusiak (1932)Wojtusiak (1932)Quaranta (1952)Neumeyer Ind. & Ja 4*Arnold Yes & Neumeyer (1987) Yes Yes *Three maxima in 4* *Gap in wavelength spontaneous mate choice training catching* of moving prey dummy response choice food training training training food training training Broadband stimuli, Broadband stimuli, phototaxis Muntz (1962,Broadband 1963) stimuli, phototaxis Jaeger & Hailman (1971); Grey Yes card experiment, food Grey card experiment, prey Spectral sensitivity, detection Grey card experiment, mate Wavelength. discrimination, Grey card experiment, food Monochromatic lights, food Wavelength discrimination, Spectral sensitivity, food , ) ) Grey card experiment, feeding spp., ) Pseudemys Clemmys ), Fire cristatus spp., gigantea Rana Pseudacris . Rana Rana . .) ), newts ) Salamandra Testudo T T , sp., sp., , .) Hyla Bufo viridis cont ) ) sp.) ) ), Crested newt cont ) ) spp., Acris alpestris salamandra salamandra vulgaris . . . , Dentrobates pumilo Scaphiopus Triturus cristatus S T S ( temporaria ( Bufo Limnaoedus sp., temporaria ( salamander ( salamandra ( ( T ( caspica elephantopus scripta Arrow poison frog Common frog ( 16 species of frog and toad Common frog ( Fire salamander Fire salamander Grey toad ( Caspian terrapin ( Giant turtles ( Freshwater turtle ( Table 2 ( Animal speciesAmphibians ( Method Reference q1 q2 q3 Comments Animal colour vision 97 . (1993) et al ) c (1998) (1998) generalization over brightness, VS receptor is used colour discrimination possible with each pairtwo of receptors (see Section V.2 vision Review: Varela Review: Jacobs (1993) * *VS receptor is used for Ind. Yes * *Colour discrimination but . (1987); . (1981) Yes * *VS receptor used for colour et al . (1990); Palacios . (1999) Yes 4 * *Colour discrimination was et al et al et al & Varela (1992) Derim-Oglu & Maximov (1994) (1994) Wagner (1932)Fleishman & Persons (2001) Yes Yes Remy & Emmerton (1989) Yes 4Maier (1992) 2* *Model Vorobyev & Osorio Yes 4 2* *Model Vorobyev & Osorio Derim-Oglu Derim-Oglu & Maximov Plath (1935)Osorio Hertz (1928) Yes Goldsmith Yes Ferens (1947)Martin (1974)Meyknecht (1941) Yes Yes Yes Friedman (1967)Hemmi (1999) Yes Yes training visual fixation reflex training training recognition recognition training adjusted light spectra, food training training food training training training training training training Moving coloured stimuli, Wavelength discriminationColour mixture Emmerton & Delius (1980) Ind. Palacios 4 Grey card experiments, nest Grey card experiments, nest Grey card experiment, food Wavelength discrimination, Monochromatic stimuli, food Monochromatic stimuli, food Neutral point, food training Hemmi (1999) Yes 2 ) Monochromatic stimuli, food ) Spectral sensitivity, food ) ) Grey card experiment with ) Grey card experiment, food ) Grey card experiment, food ) Grey card experiment food ) Grey card experiment, food ) Tree Macropus Muscicapa Archilochus Anolis Gallus gallus Leiothrix lutea Lacerta agilis (pigeon) Spectral sensitivity, food Strix aluco Melopsittacus Athene noctua Passer montanus ) Parus major ) ) ) Didelphis virginiana ) Garullus glandarius cristellatus hypoleuca alexandri sparrow ( undulatus eugenii Sand lizard ( Anole lizard ( Columba livia Pekin robin ( Pied flycatcher ( Great tit ( Budgerigar ( Chick males ( Jay ( Hummingbird ( Tawny owl ( Little owl ( Possum ( Tammar wallaby ( Birds Mammals 98 Almut Kelber, Misha Vorobyev and Daniel Osorio (1998) additional references on dog colour vision (1973) and Jacobs (1981), for more references oncolour cat vision. three cone types andtrichromatic di- colour or vision is still an unresolved question . (1987) Yes 3** . (1989) . (1989) . (1989) 2 . (1987) Yes 2** **Whether cats have two or et al et al et al et al et al cker (1957)cker (1957) Yes Yes $ $ Polson (1968)Orbeli (1909)Rosengren (1969)Neitz YesNeitz 2 Yes Yes Eisfeldt (1967)Buchholtz (1952)Bonaventure *See (1961) Rosengren (1969), for Yes Loop Yes Yes Kezeli Du Du *See Autrum & Thomas Meyer-Oehme (1957)Jacobs (1976) Yes Ind. 2 Jacobs & Neitz (1986) Yes 2 1* *Model Vorobyev & Osorio training training training traning food training training playing behaviour ng training training training training training training food training training Neutral point, food training Jacobs & Neitz (1986)Grey card experiment, food YesSpectral sensitivity, food 2 Wavelength. discrimination, Neutral point, food training Neitz Monochromatic stimuli, food Coloured lights, food trainingColoured lights, food trainingSpectral Sechzer sensitivity, & food Brown (1964) Mello & Peterson (1964)Adjusted spectra, food Grey Yes card experiment, food Yes Grey card experiment, food Grey card experiment, food Wavelength discrimination, Spectral sensitivity, food )* Grey card experiment, food ) Spectral sensitivity, food )* Grey card experiment, ) Grey card experiment, food Sciurus (Common Viverricula .) Tupaia .) Mungos Tupaia glis ) cont ) ) cont ) Fox squirrel ) Canis lupus Canis lupus familiaris Felis sylvestris niger . S ichneumon indica squirrel) griseus ( belangeri Tree shew ( Dog ( Wolf ( Cat ( Mongoose ( Indian civet ( Sciurus vulgaris Grey squirrel ( Tree shrew ( Table 2 ( Animal speciesMammals ( Method Reference q1 q2 q3 Comments Animal colour vision 99 . (2001) showed et al 1998 that sea lions andonly seals one have cone type,basis the of their colour discrimination ability therefore remains uncertain. cker (1987) Yes* $ Crescitelli & Pollack (1972)Jacobs (1978) Yes 2 Jacobs (1993) Yes 2 Yes 2 1* Model Vorobyev & Osorio Walton & Bornemeier (1938)Jacobs & Yes Neitz (1985) Griebel & Schmid (1996)Griebel & Schmid (1992) Yes Yes* *Peichl Busch & Du Grzimek (1952)Hoffmann (1952) Yes Ind. training point, wavelength discrimination, food training training training food training training training training training training Monochromatic stimuli, food Spectral sensitivity, white Spectral sensitivity, food Wavelength discrimination, Grey card experiment, food Grey card experiment, food , ) sp.) Grey card experiment, food ) ) Monochromatic stimuli, food ) mexicanus ) Grey card experiment, food . ) Grey card experiment, food S , ) ) Prairie dog Trichechus Zalophus Arctocephalus ) Equus equus Bos indicus Rattus norvegicus lateralis . Ammospermophilus leucurus Spermophilus Cynomys ludovicanus Spermophilus beecheri ( ( tridecemlienatus ( ( S manatus californicus Antelope ground squirrel Ground squirrel Ground squirrel Rat ( Manatee ( Sea lion ( Fur seal ( Horse ( Zebu ( 100 Almut Kelber, Misha Vorobyev and Daniel Osorio

V. TESTS OF COLOUR VISION way of testing colour vision is by associative learning with a food reward. Here, we list general methods Von Frisch (1914) successfully differentiated the uses according to the stimulus design and give examples of chromatic and achromatic signals by bees. of the behavioural context in which these have been Although bees and birds do not usually learn used. Table 2 gives an extensive, but still incomplete achromatic signals, mammals usually have com- list, of experiments (for older reviews see Mazokhin- paratively poor colour vision, and may prefer to use Porshnyakov, 1969; Autrum & Thomas, 1973; achromatic cues (Jacobs, 1981, 1993). For that Menzel, 1979; Jacobs, 1981, 1993). reason, many researchers failed to train mammals Three related methods for demonstrating colour like cats or dogs to discriminate colours, and until vision are described below (Section V.1), all of the 1960s it was not certain if they could see colour which predate the knowledge of receptor sensitivi- (Rosengren, 1969; Jacobs, 1981). ties: (a) discrimination of a fixed colour from a series An early method of excluding achromatic in- of grey shades; (b) discrimination of monochromatic formation was to present an animal with two stimuli colours, which can be changed in intensity; (c) dis- of different colours that were matched in brightness, crimination of two broadband stimuli that can be meaning that intensities were adjusted so they adjusted such that either one or the other emits more appeared equally bright. Early work used human photons over the entire spectrum. If an animal brightness, but it was recognized that the animal’s selects a stimulus according to its wavelength spectral sensitivity could differ from ours, and needed distribution it must have colour vision. to be measured. Stimulus intensities could then be Section V.2 describes investigations that set out to adjusted appropriately for the test species (see study which receptors and neural mechanisms Section V.2). There are several difficulties with this underlie colour vision. These include: (a) colour- approach. First, spectral sensitivity may depend matching experiments, the only direct test of the upon behavioural context (Jacobs 1981; Neumeyer, number of receptors; (b) discrimination tests with 1991). The spectral sensitivity of goldfish, for stimuli specially adjusted to test hypotheses on example, differs depending upon whether they are receptors; and (c) models of colour choices based on trained to prefer a coloured target over a dark one, discrimination tests. or a dark target over a coloured one (Neumeyer, Knowledge of discrimination thresholds allows 1991). More fundamentally, for light-adapted eyes quantitative description of colour vision, and is behavioural spectral sensitivities often are mediated discussed in Section VI. In recent years, quantitative by chromatic, not achromatic mechanisms. Adjust- models have emerged as powerful tools for under- ing intensities according to these sensitivities does standing the biological relevance of colour dis- not then exclude achromatic signals (see Fig. 5; crimination. Section VI.3). Finally, where two or more receptor types contribute to the achromatic mechanism, and (1) Evidence for colour vision are randomly arranged (as in primates) spectral (a) Grey card experiments differences can locally lead to an achromatic signal even if the intensities are properly adjusted for the Von Frisch’s (1914) ‘grey-card’ experiment with average. Given the difficulties of excluding achro- bees is a convincing demonstration of colour vision. matic signals, a more practical method is to make An animal learns to associate a reward with a colour, intensity unreliable by testing discrimination for a and then chooses between this colour and many range of relative intensities, or by adding intensity shades of grey. It is assumed that at least one grey noise. gives a sufficiently similar achromatic signal to the Colour vision tests must refer to a specific trained colour, so that if all are discriminable from behavioural context. In dim light, many vertebrates the colour the animal is not relying on achromatic lack colour vision, and directional motion vision cues. Von Frisch (1913b) also tested European is often based on signals from one spectral type minnows (Phoxinus phoxinus), and his influence led to of receptor (Schlieper, 1927; bees: Lehrer, 1993; many similar studies, especially in Germany during goldfish: Schaerer & Neumeyer, 1996). Behaviours the 1920s and 30s (Table 2). tested include feeding, mating, escape, phototaxis, There have been some interesting variants on the movement detection, camouflage, nest orientation grey card method. Swihart (1971) noted that and oviposition. Both spontaneous and learned Heliconius charitonius butterflies cannot associate a behaviour can be studied. However, the most usual medium shade of grey with food, always choosing Animal colour vision 101 the brightest, but could learn successively two widely used when testing human colour vision, and yellowish colours. Since both yellows could not both is a feature of Ishihara’s (1917) tests. Such patterns have been the brightest, the butterflies could not can be displayed on a monitor (which excludes have been using achromatic cues. An alternative ultraviolet) or printed out as paper stimuli. Osorio et explanation is that the butterflies have a preference al. (1999b) trained chicks to find food in small paper for yellow, and this directs their attention to the containers covered with such patterns, and demon- intensity of yellow objects so that they can learn the strated tetrachromatic colour vision in this bird. achromatic signal; but this too requires colour vision. Apart from associative learning, spontaneous (b) Monochromatic stimuli preferences have long been used to test colour vision. Ilse (1928) found that butterflies (various Nym- Monochromatic stimuli can be precisely defined in phalidae, Papilionidae, Pieridae and Satyridae) physical terms, and thus have long been used in prefer both blue and yellow to any achromatic shade human psychophysics (e.g. Maxwell, 1860) and with including white. On the other hand when hermit animals. If changes in relative intensity of two crabs (Eupagurus anachoretus) select a new home they monochromatic lights do not influence an animal’s prefer achromatic shells of any intensity from black choice, it must be using colour vision. Monochro- to white over blue or yellow alternatives (Koller, matic (or narrow-band) lights can be produced 1928). with monochromators, interference filters, or light- Control of body coloration by fish (von Frisch, emitting diodes (LEDs). There are three basic 1913a) and crustaceans also uses colour vision. To procedures: match their background brown shrimps (Crangon vul- (i) If the spectral sensitivity of a species is known, garis) selectively dilate red, yellow and sepia-brown the intensities of the stimuli can be adjusted to give pigmented chromophores. In tanks surrounded by equal achromatic signals, but other than with yellow paper the yellow pigment was more expanded humans this is not easy. In a careful study, Powers & than with any shade of grey surround (Koller, Easter (1978b) classically conditioned goldfish (con- 1927). In contrast, cuttlefish (Sepia officinalis) seem ditioned stimulus: respiration rate; unconditioned to be colour blind when selecting body pattern on stimulus: electric shock) to discriminate lights of coloured gravels (Marshall & Messenger, 1996). 532 nm and 636 nm whose intensities were adjusted Amphibians have multiple types of spectral re- according to a previously determined detection ceptor, but are often difficult to train by operant threshold (using separate curves for photopic and conditioning, so alternative methods are needed to scotopic sensitivities). To ensure that discrimination test colour vision. For example, toads (Bufo bufo) was not made by achromatic cues, both lights were jump towards coloured cards that resemble prey, but varied over 0n5 log units. Goldsmith et al. (1981) the response habituates. Meng (1958) found that used a similar method to test spectral discrimination toads react again if they see a novel colour, but not by black-chinned hummingbirds (Archilochus alex- a different shade of grey. The urodeles Salamandra- andri), with stimulus intensities adjusted for the salamandra and Triturus spp. also respond to moving photopic sensitivity of the pigeon. This study prey, and to test them Himstedt (1972) used an demonstrated hummingbird colour vision, because elongated window divided into two fields that they did not discriminate stimuli differing only in differed in colour or intensity. The border separating intensity. the fields moved sinusoidally. A jump towards the (ii) When spectral sensitivity is unknown – as is target indicated that the amphibian saw the border. usual – training can be done using equal (or arbi- The salamanders reacted much more strongly to a trarily chosen) physical intensities. After training, border between a coloured and any grey field than intensities in unrewarded tests have then to be varied they did to a border between two similar shades of over an (often inconveniently) large range of several grey indicating that they used colour to make the log units (e.g. Quaranta, 1952 for giant tortoises, discrimination. Fleishman & Persons (2001) used a Testudo spp.; Kelber & Pfaff, 1999 for the butterfly similar method, testing responses of lizards (Anolis Papilio aegeus). cristellatus) to movement of coloured cards that (iii) In operant conditioning, training can involve resembled the displays of conspecifics. intensity variations, and no subsequent unrewarded A variation of the grey card technique is to add tests are needed. This was how Schiemenz (1923) intensity noise to the training colours, making demonstrated that European minnow and three- brightness an unreliable cue. This technique is spined stickleback (Gasterosteus aculeatus) see UV light 102 Almut Kelber, Misha Vorobyev and Daniel Osorio and have colour vision. Operant training with operant conditioning, was used successfully to show narrow-band lights is commonly used with mammals that dogs have colour vision (Orbeli, 1909). (Table 2; Jacobs 1981, 1993). For the tammar wallaby (Macropus eugenii), Hemmi (1999) adjusted (2) Tests of visual mechanisms stimulus intensities to give equal signals for the We now turn from simple demonstrations of colour L cone, and went on to vary both rewarded and vision to tests of the underlying physiological unrewarded training intensities widely. It was clear mechanisms. Firstly, we discuss colour matching as a that the wallabies have colour vision because they direct test of the number of receptors used for colour preferred the rewarded colour to black, but black to vision, which can be done without knowledge of the colour that was unrewarded during training. receptor spectral sensitivities, and secondly tests of Spontaneous preferences for food sources or receptor inputs to visual behaviour based on knowl- oviposition substrates have been studied using edge of receptor sensitivities. monochromatic lights in butterflies (Scherer & Kolb, 1987) and hoverflies (Lunau & Wacht, 1994). (a) Colour matching Narrowband spectral stimuli have long been used to study Daphnia sp. phototaxis with controversial Colour matching is the direct test for dimensionality results (Koehler, 1924), but a recent careful study of colour vision. It is based on the principle (see (Storz & Paul, 1998) shows that Daphnia magna Section II.2) that if n receptor signals are compared phototaxis is specific to wavelength, and indepen- in colour vision, any spectral stimulus can be dent of intensity, over a large intensity range. matched with a specific mixture of n primaries. For a dichromat, a mixture of two primary spectra can match white light, a trichromat requires three and so on. (c) Broadband stimuli at different intensities Following Maxwell (1860), colour matching has When Lubbock (1888) studied Daphnia sp. he first been used widely with mammals, which are di- or found that they are positively phototactic (up to trichromatic (Jacobs, 1981, 1993). Things are more some intensity limit), and then that they prefer a complicated with increasing numbers of receptors, light source filtered with a yellow filter to the but colour-matching experiments have shown that unfiltered alternative. As the unfiltered light had a honeybees are trichromats (Daumer, 1956), and higher intensity at all wavelengths, Lubbock (1888) goldfish and pigeon tetrachromats (Neumeyer, 1985, could conclude that the Daphnia sp. have colour 1992; Palacios et al., 1990; Palacios & Varela, 1992). vision, preferring yellow to white light. He specu- It seems unrealistic to test butterflies for possible lated that this preference arises because the algae pentachromatic vision (Arikawa, Inokuma & that Daphina sp. eat colour water yellow. Subsequent Eguchi, 1987), and impossible to test a mantis experiments on phototaxis in frogs (Rana spp.), toads shrimp with 12 spectral types of photoreceptors and grasshoppers (Phaeoba sp.) resembled Lubbock’s, (Cronin & Marshall, 1989; Marshall & Ober- trading a preference for a particular waveband winkler, 1999). Even with goldfish, a two-step against a general preference for high intensities procedure was applied (Neumeyer, 1992). First, (Muntz, 1962; Jaeger & Hailman, 1971; Kong et al., three lights were used to match ‘human-white’ light 1980). Unlike Daphnia sp., both grasshoppers and missing UV and second, it was shown that goldfishes amphibians preferred short to long wavelengths. For can discriminate UV-containing white from UV- frogs, Muntz’s (1962) critical test was to present the missing white. more attractive colour together with a mixture of A special case of colour matching can be used to this light and the less attractive colour. The mixture demonstrate dichromacy (Fig. 2A; Jacobs, 1981). then had a higher intensity than the preferred For a dichromatic eye all colours are represented by colour. Since the less intense stimulus was chosen in quantum catches of two receptor types. For any these experiments, it was concluded that a chromatic broadband stimulus, including a white one, it is mechanism overrode the preference for the more possible to find a wavelength and intensity of intense stimulus. Jaeger & Hailman (1971), on the monochromatic light, which will match the quantum other hand, showed that even when the stimulus catches of both receptors. Thus, a dichromat confuses with the less attractive colour was more intense light of a specific wavelength – called the neutral than the other at all wavelengths it remained point – with white light (Jacobs, 1981, 1993; less attractive. A similar stimulus design, but with Hemmi, 1999). Animal colour vision 103

(b) Discrimination of specially adjusted stimuli response can be related to receptor signals by general linear models. If photoreceptor spectral sensitivities are known One such model has been used to study mate photoreceptor quantum catches can be calculated choice in toads (Bufo viridis). Relative preferences for (see Section II.3), and it is possible to design stimuli a series of pairs of coloured toad-like objects were giving known quantum catches in the different measured in dual-choice tests (Orlov & Maximov, receptor types. For instance, two stimuli can be 1982). Colour preferences were fitted by a model chosen to give equal quantum catches in one or even (Losev & Maximov, 1982), which assumed that two spectral types of receptor. If an animal is still preference (X) depends on a weighted sum of able to discriminate the two colours, this is good receptor quantum catches. It was found that evidence that an additional receptor type is involved. excitation of the ‘green’ rods (see Table 1) increases This approach has provided evidence for trichro- attractiveness, while excitation of long (L) and macy in cats, which are commonly thought to be medium (M) cones decreases it. A linear model cone dichromats (Loop, Millican & Thomas, 1987; nicely explained the preferences: Jacobs, 1993). Electrophysiological evidence indi- cates that in photopic conditions cat ganglion cells X l 0n1 qSRk0n22 qMk0n1 qL, (5) receive input from three spectral types of photo- where qSR, qM and qL are quantum catches of the receptor, maximally sensitive at 450 nm, 555 nm toad’s green rod, M and L cones, respectively. (typical mammalian S and L cones), and at 500 nm, Backhaus (1991) trained bees to coloured stimuli which is typical for rods (Ringo et al., 1977; Crocker and tested them with several similar colours sim- et al., 1980). To find out whether the 500 nm ultaneously. A multidimensional scaling procedure receptor is used for colour vision, Kezeli et al. (1987) was used, and choice proportions assumed to depend trained cats to discriminate a group of green from a on the distance in colour space, ∆S, between the group of purple stimuli. Both groups of colour stimuli, which in turn was dependent on the linear occupied the same area in the cat’s two-dimensional combinations of receptor signals. Two scales, A and dichromatic colour space given by S and L cones, B, were needed to describe the data. The distance is but differed substantially for a putative 500 nm given by: receptor. To take account of differences between calculated and actual cone sensitivities, stimulus ∆S l QAQjQBQ, (6) colours were varied so that for any reasonable where hypothesis about S and L sensitivities a dichromat would fail to discriminate at least some of the green A lk9n86 ESj7n70 EMj2n16 EL, (7) stimuli from the purple. In fact, cats reliably B lk5n17 ESj20n25 EMk15n08 EL, (8) discriminated purple from green, implicating a third and Ei l qi\(1jqi) denotes the receptor excitations, input. Kezeli et al. (1987) argued for a 500 nm cone which are related by non-linear transformations to type (photopic) receptor, but rods cannot be receptor quantum catches qi. The scales A and B excluded. describe chromatic mechanisms, because receptor Where spectral sensitivities of receptors are known signals are combined with opposite signs. and do not overlap too much it is possible to adjust Finally, Kelber (1999, 2001) studied oviposition illumination so that only a subset of receptors are in a butterfly (Papilio aegeus), and found that active in an experiment. Osorio et al. (1999a) used preferences amongst a number of colours are this method with domestic chicks, choosing stimuli described by a model assuming that choice propor- and illumination so that only two receptor types tions depend on only one linear mechanism (η) were active in each experiment. They found that receiving signals from three receptor types such that: chicks probably use all four single cone types for colour vision, and that the receptors drive at least η lk1n24 qSjqMk0n77 qL. (9) three chromatic mechanisms. VI. MODELLING THRESHOLDS FOR COLOUR c Receptor based models of colour choices ( ) - DISCRIMINATION Given receptor sensitivities it is possible to establish the receptor inputs to visual responses and the Section V discussed the existence of colour vision and underlying achromatic and\or chromatic mechan- studies based on comparing relative preferences for isms. Specifically, the strength of a behavioural different colours. Models have been found to be 104 Almut Kelber, Misha Vorobyev and Daniel Osorio helpful in describing colour vision mechanisms in achromatic point), while wavelength discrimination various behavioural contexts. If models fit the gives thresholds about many points. This means that behavioural data well, we can then look for a modellingspectralsensitivitydoesnotrequireassump- physiological correlate of the postulated neural tions about changes of threshold values across colour mechanisms. At the same time, quantitative models space (Appendix A; Section VI.3). Secondly, the can be used to test hypotheses about the evolution highly saturated colours used for wavelength dis- and the ecological value of specific colour vision crimination may saturate opponency mechanisms, systems. as they do in humans (Mollon & Este! vez, 1988). An advantage of studying thresholds for colour Saturation introduces non-linearities, which com- discrimination is that it is generally easier to estab- plicates modelling. lish whether or not an animal can discriminate two colours than to ask how different they look. (2) Interpretations of the shapes of Also, non-linearities are usually less important near threshold sensitivity curves threshold. This makes it easier to fit quantitative models to behavioural data, which may reveal the Data on discrimination can give information about neural mechanisms underlying colour vision and the mechanisms of colour vision. Early analysis of how they limit behavioural judgements. behavioural spectral sensitivity and wavelength discrimination asked questions about receptor mech- anisms, rather than subsequent neural processing (1) Measuring thresholds (von Helversen, 1972; Maier, 1992). These interpre- Generally, it is more difficult to measure accurate tations assumed that: (i) local maxima of be- thresholds for animals than for humans, thus havioural spectral sensitivity correspond to maxima behavioural thresholds have been measured only in of receptor sensitivities; and (ii) wavelength dis- a small number of species (see Table 2), including crimination is best where the sensitivities of receptors several mammals (Jacobs, 1981, 1993), honeybees overlap, i.e. midway between receptor sensitivity (von Helversen, 1972) and goldfish (Neumeyer, peaks. The number of receptors, and their spectral 1984, 1985, 1986, 1992). The measurements require tuning can then be inferred from spectral sensitivity precise stimulus intensities and spectra, such as mono- and wavelength discrimination functions. In honey- chromatic lights. Thresholds are usually measured bee, goldfish and turtle this method has allowed in one of two ways, either as spectral sensitivity or determination of the number of receptors involved in as wavelength discrimination. Spectral sensitivity colour vision, before the corresponding photorecep- is given by the minimal intensity of monochromatic tors were directly recorded (Daumer, 1956; Neu- light that can be detected, on either a dark or an meyer, 1984, 1985; Neumeyer & Ja$ ger, 1985). Bees achromatic background, sensitivity being the inverse have three maxima in their spectral sensitivity curve of threshold intensity. In physiological measure- and two minima in the wavelength discrimination ments, absolute sensitivity is often measured; in curve indicating that they use three receptor types. behavioural tests, an achromatic background is more Goldfish and turtle have four maxima in their appropriate since many animals would not respond spectral sensitivty curve and three minima in their in complete darkness. In effect the task is to detect wavelength discrimination functions, which indi- very unsaturated colours. Wavelength discrimi- cated that they had a fourth VS receptor, which was nation (∆λ\λ function) is defined as the smallest then unknown (Neumeyer, 1985, 1986, 1992; Neu- wavelength difference that can be discriminated meyer & Ja$ ger, 1985). The UV maximum in spectral using two monochromatic stimuli. Monochromatic sensitivity had previously been attributed to the stimuli might be discriminated by both chromatic β-peak of the other (S, M and L) visual pigments and achromatic signals, but studies of wavelength (Beauchamp & Rowe, 1977). discrimination are generally intended to isolate As well as identifying receptor types, behavioural chromatic mechanisms, in which case stimulus spectral sensitivities (without quantitative model- intensities are adjusted to remove achromatic signals, ling) can implicate neural interactions between although this adjustment is difficult (Section V.1b). receptor outputs. The simplest possibility is that On the whole, spectral sensitivity is better suited receptor signals from two stimuli (Fig. 1, stage 3) are to quantitative analysis than wavelength discrimi- compared without opponency (Fig. 1B). This pre- nation. Firstly, spectral sensitivity gives thresholds dicts that peaks of the behavioural spectral sensitivity about one point in colour space (normally the curves should be at least as broad as the receptor Animal colour vision 105

peaks. Neumeyer (1984) found that peaks of the behavioural spectral sensitivity curve of goldfish were in fact narrower than those of its photorecep- tors, and deduced that there are inhibitory inter- actions between receptor signals (Fig. 1A, stage 2).

(3) Metric spaces and quantitative analysis of threshold data Helmholtz (1896) introduced quantitative mod- elling of thresholds (Wyszecki & Stiles, 1982). The theory assumes that discriminability of any two colours is given by their separation in some colour space, ∆S, and that the behavioural response, Pcorr (Fig. 1, stage 4), depends on ∆S alone. Where ∆S is below a threshold value, colours are assumed to be indistinguishable. In two-alternative forced-choice tests Pcorr can vary from 0n5 (random choice) to 1 (100% reliable choice), and threshold is usually assumed to correspond to Pcorr l 0n75. It is im- portant to note that distances (∆S) refer to dis- criminability of stimuli, and say nothing about perceptual similarity of stimuli that are 100% discriminable. In a given space, the rule for calcu- lating distance between points is called the ‘metric’ of the space. Different metrics make different assump- tions about the processing of receptor signals (Fig. 1, stage 2), and about the comparison of neural signals corresponding to two colours (stage 3). Many models have been developed to explain human colour discrimination, some of which have been applied to animals. A given metric model is fitted to colour dis- Fig. 3. Diagrams of contours of equal colour discri- crimination data by describing a contour of equal minability in trichromatic receptor space. Different discriminability, corresponding to a given value of contours are predicted by three models that have been Pcorr, about each location in a colour space. That is, used to fit experimental data (Fig. 5; Brandt & Vorobyev, all points on the contour are equally well discrimi- 1997). The axes of the space correspond to quantum nated from the central colour. Different metric catches of short (S), medium (M) and long (L) models predict different contours (Figs 3, 4). The wavelength-sensitive receptors. (A) One achromatic mechanism is used for colour discrimination, where the # distance in colour space ∆S is given by ∆S l # (kS ∆qSjkM∆qMjkL ∆qL) . The three positive coefficients positive coefficients (i.e. gSS, gMM, gLL) denote the (i.e. kS, kM, kL) denote the weights of the inputs of components of metric tensor fitted to experimental data. receptors to a mechanism, that might be deduced by A contour of equal discriminability is ellipsoidal with axes fitting the model to experimental data (see Fig. 5). The parallel to the receptor axes. (C) Discrimination is limited dotted line indicates the axis in the colour space by the most sensitive receptor mechanism. This is an corresponding to this mechanism. The two planes upper envelope model without interactions between orthogonal to the mechanism’s axis give contours of equal receptor mechanisms. Distance in this colour space is discriminability. (B) Discrimination is limited by noise in given by ∆S l Max(Qki∆qiQ), where the three positive the three receptor mechanisms, with stage 2 mechanisms coefficients, ki (i l S, M, L), denote the sensitivities of (see Fig. 1) absent or not adding noise. This is a receptor mechanisms. Contours of equal discriminability Helmholtz line element. Distance in this colour space is are described by a parallelepiped with sides parallel to the # # # # given by ∆S l gSS ∆qSjgMM ∆qMjgLL ∆qL. The three receptor axes. 106 Almut Kelber, Misha Vorobyev and Daniel Osorio

Fig. 4. Contours of equal discriminability in the chromaticity diagram of a trichromatic receptor space. (A) Colour (Maxwell) triangle (see Fig. 2B) specified by the surface in receptor space of a plane crossing receptor axes (rep- resenting quantum catches of receptors, qS, qM and qL), at coordinates (1,0,0), (0,1,0) and (0,0,1). The chromaticity locus, qc, of a colour is the intersection of a line connecting the location of the colour in the receptor space, Q, with the origin and the triangle. (B) Spectral loci (in nm) for the honeybee in a colour triangle. See Fig. 2B. Axes X" and X# of the chromaticity diagram are given in Appendix A, equations (A3) and (A4). (C) Contours of equal dis- criminability plotted in the colour triangle shown in B. The ellipse is predicted by a line element model (Fig. 3B), # # # where the distance in the colour space is: ∆S l g"" ∆X"j2g"# ∆X"∆X#jg## ∆X#. ∆Xi (with i l 1, 2) denotes the difference in the chromaticity co-ordinates, and gik (with i, k l 1, 2) the components of a metric tensor that can be fitted to experimental data (see Fig. 5). The parallelogram describes the contours of equal discriminability predicted by dominance and city-block metrics. The dominance metric predicts a parallelogram with its sides (and axes, dashed lines) parallel to the axes of the mechanisms mediating discrimination (e.g. receptor or colour opponent signals). Alternatively, the city block metric postulates that diagonals of the parallelogram correspond to these axes (dotted lines). A parallelogram can be defined by four parameters describing the length and orientation of its sides. Con- sequently, dominance and city-block metrics for trichromatic colour space have four parameters, while an elliptic model has three. (D) A chromaticity diagram corresponding to a receptor-noise-limited colour opponent model (see Section VI.3b; Appendix B). The axis X" is collinear to the base of colour triangle (in B), while the orientation of X# in the triangle plane depends on the noise in receptor mechanisms. For thresholds plotted in this chromaticity diagram (see eqns A3 and A4), the model predicts circular contours of equal discriminability. most parsimonious approach to calculating distance, Moed, 1983) and city block metrics (Backhaus, known as a line element, uses a Riemann metric, 1991). which is a generalized Euclidean metric (Wyszecki & Stiles, 1982). Line element models predict (a) Inferring neural mechanisms from threshold data ellipsoidal contours (Figs 3B, 4C). On the other hand, two types of Minkowski metric predict An important reason for fitting metric models to polygonal contours (Figs 3C, 4C), these are domi- behavioural threshold data is that, in principle, they nance (Sperling & Harwerth, 1971; Nuboer & can give information about neural mechanisms at Animal colour vision 107

Fig. 5. (A) Predictions of models of colour discrimination (solid lines) fitted to honeybee spectral sensitivity data (filled circles; von Helversen, 1972). Geometrical interpretations of the models are illustrated in Figs 3 and 4. In each case, curves are least-squared best-fits for the model in question. (i) Discrimination by an achromatic mechanism (Fig. 3A). (ii) Discrimination limited by receptor noise without interactions between receptors (Fig. 3B). (iii) Discrimi- nation limited by the most sensitive receptor mechanism, without interactions between receptors (Fig. 3C). (iv) Dis- crimination by two chromatic mechanisms (ellipse in Fig. 4C), and also dominance and city block models (paral- lelogram in Fig. 4C), which are indistinguishable for these data (see Section VI.3). Modified from Brandt & Vorobyev 1997. Only curve iv accurately describes the honeybee’s colour thresholds. (B) Spectral sensitivities of three vertebrates as predicted by the receptor-noise-limited colour opponent model (as curve iv above; see Appendix B): a dichromat, the tree shrew (Tupaia belangeri; Jacobs & Neitz, 1986); a trichromat, human (Sperling & Harwerth, 1971); and a tetrachromat, Pekin robin, (Leiothrix lutea; Maier, 1992). Each study had two subjects, indicated by separate symbols (o, j). Curves are displaced on the vertical axis for clarity. Modified from Vorobyev & Osorio (1998). the stage in the visual pathway that limits per- contours says nothing about the receptor inputs to formance. In practice, however, different models – stage 2 mechanisms. For the models where dis- that might implicate quite different physiological crimination thresholds are described by polygonal mechanisms – often make similar predictions, so that contours (dominance metric and city block metric very accurate behavioural measurements are needed models; Figs 3, 4), the receptor inputs to neural to distinguish between them (Fig. 5). Sufficiently mechanisms can be derived from the orientation of accurate measurements are hard to obtain from most the sides of polygons in the colour space (Brandt & animals. Vorobyev, 1997). However, for models where the A key question is whether limits to colour discrimination thresholds are described by ellipsoidal discrimination are imposed at the receptor stage contours (Riemann metric; Fig. 3B), the receptor (Fig. 1, stage 1), or by subsequent neural stages inputs to neural mechanisms cannot be derived from (stages 2, 3). When noise originating in the receptors the orientation of the main axes of the ellipse. This is limits the discriminability, the shape of threshold because an appropriate transformation of the colour 108 Almut Kelber, Misha Vorobyev and Daniel Osorio space maps the ellipsoid onto a sphere, whose main assume that receptor signals do not interact (Fig. 1B) axes are not defined (Fig. 4D; Brandt & Vorobyev, fail to explain the data. This implies that receptor 1997). signals are integrated by some neural mechanism Ellipsoid models (Riemann metric) make very (Fig. 1, stage 2) before responses to different stimuli general assumptions about neural mechanisms of are compared (stage 3). Likewise, single-mechanism colour discrimination. They are valid if: (i) post- models – such as those described in Section V.2.c – receptoral neural interactions (Fig. 1, stages 2 and 3) do not fit the data. To explain honeybee spectral are smooth functions, and threshold stimuli are sensitivity one needs to assume at least two stage 2 reasonably close together in receptor space (Brandt mechanisms, which must be insensitive to intensity and Vorobyev, 1997, Appendix A); or (ii) behav- variation, and involve chromatic interactions be- ioural thresholds are set by noise in neural mech- tween receptor signals. anisms (Vorobyev & Osorio, 1998, Appendix A). Of the polygonal models, the dominance metric is (b) Receptor noise and colour thresholds one of the earliest models of colour vision, postulating that the receptors do not interact (stage 2 is absent; The best vision can do is to meet a limit set by the Fig. 1B). Colour vision can then be described without noise originating in the photoreceptors. Actual assuming opponent interactions. This model pro- performance is worse than this limit because receptor poses that the most sensitive receptor mechanism is signals are corrupted by noise originating more used for detection of any given stimulus. The upper proximally in the visual pathway. One may expect envelope of the receptor sensitivities then describes receptor noise to set thresholds because phototrans- behavioural spectral sensitivity (Pirenne, 1962). The duction is metabolically costly (Laughlin, de Ruyter dominance metric – with or without interactions van Steveninck & Anderson, 1998), so that if it were between the receptors – is the simplest case of a not limiting selection would simply reduce expen- probability summation model whereby the prob- diture on phototransduction. In this context, it is ability of detection (discrimination) is given by the perhaps surprising that the predictions of classical sum of probabilities of detection by independent line element models (Helmholtz, 1896) that invoke mechanisms. In the city block metric model, the receptor limits to colour discrimination do not in fact absolute values of the differences in the neural fit experimental data (Figs 3B, 5A). signals are summed and this sum is taken as a A new model of colour discrimination thresholds measure for the discriminability of two stimuli. (Fig. 5A) suggesting a minor modification of the Polygonal models have been used to find stage 2 noise-limited models discussed so far (Vorobyev & mechanisms. Sperling & Harwerth (1971) fitted a Osorio, 1998; Appendix B) fits experimental data dominance metric model to monkey and human well. It takes account of the ‘ecological’ consider- spectral sensitivities. Later Nuboer & Moed (1983) ation that chromatic signals are more reliable than used a similar approach to make inferences about achromatic. We have mentioned that both bees and post-receptoral mechanisms from spectral sensitivity birds use chromatic signals for colour discrimination in the rabbit (Oryctolagus cuniculus). Backhaus (Section IV). Accordingly, the model assumes that (1991) fitted a city block metric model to honeybee performance is limited by receptor noise, but also colour discrimination (Section V.2c; Fig. 5). that colour is coded exclusively by opponent (chro- Polygonal models of colour thresholds have more matic) mechanisms that are insensitive to intensity parameters than ellipsoid models. Therefore, before differences. Noise in the opponent signals is set by (or invoking a polygonal model, it is desirable to show equals) receptor noise. The only model parameters that thresholds are significantly less well fitted by an are the noise levels in the receptor signals, which can ellipsoid (Figs 3B, 4C). In reality, given the scatter of either be measured physiologically or estimated from experimental data, it is difficult to distinguish the relative number of photoreceptor cells. Conse- between ellipsoidal and polygonal models (Fig. 5). quently, the model has no free parameters, and its For example, ellipsoidal models fit the thresholds for predictions can be compared directly with behav- both humans (Poirson & Wandell, 1990) and bees ioural data. It does indeed fit behavioural spectral (Brandt & Vorobyev, 1997) almost as well as sensitivities of birds, mammals and insects (Fig. 5; polygonal models (Fig. 5). Vorobyev & Osorio, 1998). For the honeybee, the Brandt & Vorobyev (1997) tested a number of model predicts the absolute value of thresholds from models on von Helversen’s (1972) measurements of noise measured by electrophysiology (Vorobyev et honeybee spectral sensitivity (Fig. 5). Models that al., 2001). Animal colour vision 109

The applicability of this receptor-noise-limited signals and colour vision are important for recover- colour opponent model indicates that its assumptions ing object surface properties under variable illumi- hold for a variety of animals. However, for verte- nation. brates the model often fails to predict thresholds in (4) A variety of methods can demonstrate colour dim light (above cone threshold), almost certainly vision without knowledge of underlying receptors or because the achromatic signal is used (Vorobyev & neural mechanisms. Osorio, 1998). (5) Knowledge of photoreceptor sensitivities per- mits the use of simple experimental methods to demonstrate colour vision, to determine the number (4) Threshold models as a tool to study the of receptors involved and to investigate subsequent biological relevance of colour vision neural processing. (6) Knowledge of photoreceptor sensitivities, be- The traditional use of threshold models is to test haviourally measured spectral sensitivities and hypotheses about physiological mechanisms, al- models together build a powerful tool for studies of though as we have seen (Fig. 5) different mechanisms the ecology and evolution of colour vision. can give quite similar predictions. A second use is to investigate the ecology, evolution and design of colour vision. For example, it is now easy to measure VIII. ACKNOWLEDGEMENTS spectra of natural objects such as food plants or bird plumage. Given an accurate model of performance, one can compare the suitability of different types of We gratefully acknowledge Simon Laughlin’s construc- tive comments on an earlier version of the manuscript, eye for tasks such as discriminating among a set of they helped to make the paper readable! Thanks to Tom spectra, or detecting them against the background. Cronin, to Justin Marshall and to everybody in the Lund This is especially worthwhile if performance is Vision Group for inspiring and helpful discussions! This limited by photoreceptor noise, because photorecep- work was supported by a grant from the Swedish Research tor spectral sensitivities are known for many different Council to A.K. and by N.S.F. grant no. IBN 9724028 to animals (Table 1), and one can often make a T. W. Cronin and NIH grant no. ROI EY0669 to J. Troy. reasonable estimate of their relative noise levels (Vorobyev & Osorio, 1998). For example, recent studies have asked how well IX. APPENDIX A: COLOUR SPACES dichromatic and trichromatic eyes would serve a primate looking for fruit against a background of Graphical representation of colour is useful for leaves (Osorio & Vorobyev, 1996; Sumner & describing experimental data and for modelling Mollon, 2000). Pursuing this idea one can also colour thresholds. (Such representations do not model the performance of hypothetical eyes, where predict thresholds.) Since colour can be defined by for example visual pigment spectral sensitivities are the set of n receptor quantum catches it can be shifted, e.g. in birds without oil droplets (Vorobyev represented as a point in the n-dimensional colour et al., 1998). Finally, we can also ask how a specific space (Fig. 2). For trichromatic vision, colour can be light habitat could influence the evolution of presented as a point (Q) in the three-dimensional receptor sensitivities (Chiao et al., 2000). receptor space, where quantum catches of the long- wavelength (Q L), middle-wavelength (Q M) and short-wavelength (Q S) are placed along the co- ordinate axes. Where receptor sensitivities are known VII. CONCLUSIONS quantum catches can be easily calculated for any light stimulus (equation 1). Generally, it is con- (1) Animals of all major phyla have multiple venient to use a co-ordinate system (qi), where visual pigments and photoreceptor types. quantum catches for stimuli are divided by those for ! (2) Most animals with multiple receptors use a reference stimulus or the background, Qi, to give a colour vision. receptor contrast space (Cole, Hine & McIlhagga, (3) Achromatic signals and chromatic signals 1993): probably yield different types of information in natural conditions, and may generally be repre- Q i qi l !.(A1) sented by separate neural mechanisms. Chromatic Qi 110 Almut Kelber, Misha Vorobyev and Daniel Osorio

If the reference corresponds to a background of a E N2 G S: 0, ; colour stimulus, equation A1 is a model of chromatic N3 adaptation. It is the simplest algorithm of correction F H for changes of illumination (colour constancy), E 1 N2 G M: k ,k ; allowing independent rescaling of receptor signals, F N2 2N3 H (von Kries, 1905), and is used widely to model E 1 N2 G colour constancy (Hurlbert, 1998; Do$ rr & Neu- L: , .(A5) N k N meyer, 2000). This is because for an eye viewing a F 2 2 3 H reflecting surface, quantum catches change with changes of illumination but the rescaled receptor Maxwell’s triangle is the most commonly used signal (equation A1) changes substantially less. diagram used in studies of trichromatic animals. Instead of the receptor space, ‘chromaticity’ However, in physiologically oriented studies it may diagrams are often useful (Fig. 2; Wyszecki & Stiles, be convenient to use axes corresponding to op- 1982). In these diagrams, the intensity or achromatic ponency mechanisms. For humans and trichromatic dimension is removed so that the location of a light primates the luminance mechanism is driven by the stimulus does not depend on its intensity, conse- summed M and L cone signals; the ‘yellow–blue’ quently they have one dimension less than the opponency mechanism compares signals of S cones corresponding colour space. Chromaticity diagrams with signals of both L and M cones, and the were introduced because humans perceive chromatic ‘red–green’ mechanism compares L and M signals. aspects of colour (hue and saturation) to be The existence of separate pathways corresponding to substantially independent of intensity. Nonetheless, these three mechanisms is established by psycho- chromaticity diagrams reduce the information about physical and physiological studies of trichromatic colour, and are useful only for animals with separate primates (Jameson & Hurvich, 1955; Krauskopf et chromatic and achromatic signals. For trichromatic al., 1982; Dacey, 2000). Unfortunately, for other eyes a common two-dimensional representation is to species the directions of opponency mechanisms are unknown. MacLeod & Boynton (1979) proposed a plot the unit plane, Q SjQ MjQ L l 1, of the receptor space (Figs 2B, 4A). A line connecting the two-dimensional diagram, with axes corresponding origin with the point Q or its extension must intersect to ‘red–green’ and ‘yellow–blue’ mechanisms: c the unit plane at a point q , whose receptor co- (LkM)\(LjM) l (Q LkQ M)\(Q MjQ L), (A6) ordinates are given by: S\(LjM) l Q S\(Q MjQ L). (A7) c Qi qi l ,(A2)Note that the position of a point on this diagram is Q SjQ MjQ L normalized similarly to that of the Maxwell triangle, and is thus independent of light intensity. A modi- where i l S, M, L. This intersection gives a stereo- fication of this diagram uses log-transformed axes graphic projection of the point Q onto the unit (Regan et al., 1998). plane. The location of that point determines the For tetrachromatic vision (Fig. 2C) colour spaces chromaticity of the colour, whereas the length of the are four-dimensional, and corresponding chroma- vector characterizes its luminosity or brightness. ticity diagrams three-dimensional. Generalisation This chromaticity diagram is an equilateral triangle, of the Maxwell triangle gives a tetrahedron (e.g. and is called the Maxwell triangle after its inventor. Goldsmith, 1991). A three-dimensional stereo- To plot a point in the plane of a Maxwell triangle it graphic projection onto unit three-dimensional is convenient to use Cartesian axes: space, QVSjQ SjQ MjQ L l 1 is given by:

1 c c c Qi X" l (qLkqM), (A3) qi l ,(A8) N2 Q VSjQ SjQ MjQ L

E c c G N2 c (qLjqM) where i l VS, S, M, L. To plot points in the three- X# l qSk .(A4) N3 F 2 H dimensional space, it is convenient to use the following co-ordinates: Note that these axes are not related to opponent mechanisms. The vertices of the triangle have the 1 c c X" l (qLkqM), (A9) following co-ordinates: N2 Animal colour vision 111

E c c G N2 c (qLjqM) deviation of the noise in the receptor mechanism, ei, X# l qSk , (A10) N3 2 and need not contain Fαi. For stimuli close to an F H achromatic background, if assumptions i–iii hold, E c c c G N3 c (qLjqMjqS) colour distance is given by the following equations X$ l qVSk . (A11) 2 F 3 H (Vorobyev & Osorio, 1998): c # The X and q co-ordinates are related by trans- # (∆fLk∆fS) i i (∆S) l # # , (B2) formation of rotation. The vertices of this colour (eS) j(eL) tetrahedron are located at: # (∆S) l E N3 G E N2 1 G # # # # # # VS: 0, 0, ;S: 0, ,k ; eS(∆fLk∆fM) jeM(∆fLk∆fS) jeL(∆fSk∆fM) 2 N3 2N3 # # # , F H F H (eSeM) j(eSeL) j(eMeL) E 1 N2 1 G (B3) M: k ,k ,k ; N2 2N3 2N3 # # # F H (∆S) l ((eS eVS) (∆fLk∆fM) E G # # 1 N2 1 j(eM eVS) (∆fLk∆fS) L: ,k ,k . (A12) N2 2N3 2N3 # # F H j(eS eM) (∆fLk∆fVS) # # Commercial software can plot three-dimensional co- j(eS eVS) (∆fMk∆fS) ordinates (Fig. 2C). # # j(eL eS) (∆fMk∆fVS) # # j(eL eM) (∆fSk∆fVS) ) # # X. APPENDIX B. RECEPTOR-NOISE-LIMITED \((eS eM eL) j(eVS eM eL) # # COLOUR OPPONENT MODEL j(eVS eS eL) j(eVS eS eM) ), (B4)

The model (Vorobyev & Osorio, 1998) is based on for di-, tri- and tetra-chromatic vision, respectively. three assumptions: (i) For a visual system with n Receptor signals are functions of the receptor quantum catches, and two simple models relating receptor channels colour is coded by nk1 unspecified opponent mechanisms, the achromatic signal is the receptor signals to quantum catches can be disregarded. (ii) Opponent mechanisms give zero considered: (i) a linear relationship (Vorobyev & signal for stimuli that differ from background only in Osorio, 1998); (ii) a log-linear relationship (Voro- intensity. (iii) Thresholds are set by receptor noise, byev et al., 1998, 2001). Because results of the model and not by opponent mechanisms. calculations do not depend on the units in which The model has the following mathematical for- receptor signals are measured, receptor signals can be re-scaled so that they are related to quantum mulation. Let fi be the signal of receptor mechanism catches, q (equation A1) by f l q or f l ln(q ) for i, ∆fi the difference in receptor signals between two i i i i i stimuli, and ∆x the difference in colour opponent the linear or log-linear models respectively. Note α that for stimuli which are close to a reference, both mechanism, α. Generally, ∆xα is given by a linear combination of the differences of receptor signals, i.e. models make the same predictions. For the log-linear model, noise in the receptor mechanism, ei, equals n the Weber fraction of the corresponding mechanism, ∆xα l  Fαi ∆fi (B1) i=" ωi (Vorobyev et al., 2001). If receptor signals are linearly related to quantum where the coefficient Fαi describes the input of catches, modeled chromatic signals remain insen- receptor i to opponent mechanism α. If opponent sitive to stimulus intensity only in the vicinity of the signals only are used for discrimination, then the achromatic point. 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