Stevens • Confusion and illusion
be advantageous; for example, allowing the weak to bluff resource
holding potential without revealing the tell-tale signs of a liar or
allowing some of us to view the glass as half full, whereas other
see it as half empty. Thus, sometimes, we do not see the world as
it is because we lack the necessary perceptual machinery and other
times because selection favors a deceptive view of the world.
Numerous studies have shown how constraints on sensory end
organs (eyes, ears, and noses) influence a receiver’s response to signals and how these receiver biases, in turn, shape the evolution of
signal design (reviewed in Ryan and Cummings 2013). But these
end organs are where perception begins, not where it ends, as
biases in perception pile up at all levels in the brain. Sometimes,
these biases are so extreme we call them illusions. As Guilford and
Dawkins (1991) pointed out in a paper of monumental importance
to this field, “Even in perception of lightness and colour, the brain
distorts incoming sensory data to construct its own illusory version of the world outside” (see also Rosenthal 2007). This is the
focus of the review by Kelley and Kelley (2014): what visual illusions do the brain create, how do these illusions influence receiver
responses to signals, and how do senders evolve signals to exploit
these illusions?
The authors make it clear that we know much more about the
psychology of illusions as it applies to signals directed at predators
than as it applies to social signals. Disruptive coloration, threatening
eye spots, startle signals, and memorable colors of prey all tweak
the predator’s psychology to enhance the prey’s survivorship. This
wealth of knowledge contrasts greatly with the sparsity of such
studies of social and especially sexual interactions. True, Endler,
and his colleagues (Endler et al. 2010) argue that male greater
bowerbirds arrange their bower decorations to elicit the illusion of
forced perspective from females viewing the court from the bower.
But much of the current work on visual biases in mate preferences
has not advanced much since Endler (1978) drew our attention to
the importance of visual signals from the receiver’s point of view
and proscribed a method for quantifying this phenomenon in the
context of signal colors and contrast (Endler 1990). These studies
advanced the field by integrating photoreceptor sensitivity with
putative color opponency systems to understand how signals evolve
to enhance contrast (reviewed in Ryan and Cummings 2013). But
the majority of these studies stop at the periphery; they do not
show that the visual contrast models predict receiver responses in
the target species nor do they conduct the behavioral experiments
necessary to reveal how the signals are perceived by the brain and
what, if any, illusions they instantiate.
The review by Kelley and Kelley (2014) combined with the
insightful review of visual signaling by Rosenthal (2007), hopefully,
will mark a new chapter in studies of visual ecology by reminding us
that all visual tracts lead to the brain and that the biases in percepts
generated by the brain, whether illusory or not, contribute to the psychological landscapes that shape the evolution of signal design.
Address correspondence to M.J. Ryan. E-mail: [email protected].
Received 27 January 2014; accepted 12 February 2014; Advance Access
publication 12 March 2014.
doi:10.1093/beheco/aru036
Forum editor: Sue Healy
References
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11:319–364.
467
Endler JA. 1990. On the measurement and classification of colour in studies of animal colour patterns. Biol J Linn Soc. 41:315–352.
Endler JA, Endler LC, Doerr NR. 2010. Great bowerbirds create theaters with forced perspective when seen by their audience. Curr Biol.
20:1679–1684.
Guilford T, Dawkins M. 1991. Receiver psychology and the evolution of
animal signals. Anim Behav. 42:1–14.
Kelley LA, Kelley JL. 2014. Animal visual illusion and confusion: the
importance of a perceptual perspective. Behav Ecol. 25:450–463.
Rosenthal G. 2007. Spatiotemporal dimensions of visual signals in animal
communication. Annu Rev Ecol Evol Syst. 38:155–178.
Ryan MJ, Cummings ME. 2013. Perceptual biases and mate choice. Annu
Rev Ecol Evol Syst. 44:437–459.
Trivers R. 2011. The folly of fools: the logic of deceit and self-deception in
human life. New York: Basic Books.
Exploring the perceptual canvas of signal
evolution: comment on Kelley and Kelley
Darrell J. Kemp and Thomas E. White
Department of Biological Sciences, Macquarie University, North
Ryde, New South Wales, 2109, Australia
Albert Einstein once famously remarked that “reality is merely an illusion, albeit a very persistent one.” In the hallmark of Einstein, this
simple phrase encapsulates worlds of conceptual complexity across
physics, biology, psychology, and philosophy. From a biological perspective, the essence of this idea is that an individual’s perceptual reality presents a mere caricature of its objectively verifiable existence.
This can be readily appreciated through situations where individual
perception obviously departs from objective reality, as in the case of
many popular human visual (optical) illusions. Such images intrigue us
because our perception of them so starkly contrasts with our cognitive
understanding of what is actually true. That is, they reveal how our
brains can err in making sense of the world around us.
In their review, Kelley and Kelley (2014) consider the potential role
of visual illusions in the biological world. That the human perceptual
system builds verifiably imperfect caricatures of reality suggests the
same for other organisms, which presents intriguing possibilities for
visual communication. Could the appearance of prey be adaptively
shaped to elicit illusionary perception in predators? Could mating
signals have evolved to push the envelope of sexual advertisement
through illusion? Could deceptive signals such as prey lures take
advantage of such perceptual tricks? The overwhelming message
from Kelley and Kelley’s review is that—for most systems—current
knowledge is too sparse to convincingly tell. There is, nevertheless, value in posing such issues to behavioral ecologists, not in the
least because they force explicit consideration of perception as the
ultimate canvas for signal evolution (see, e.g., Endler et al. 2010).
Behaviorists have increasingly accounted for the visual capabilities of
relevant viewers (e.g., Stoddard and Prum 2011), thereby more accurately characterizing signal reception, but true perception only occurs
once the eye’s neurally encoded outputs arrive in the brain.
Empirically, the key issue is how to appraise perceptual illusions in
the broader world. Humans identify such phenomena as mismatches
between perception and cognitive expectation. The challenge with
nonhuman animals is that we have an extremely limited basis for
predicting when and how such mismatches might actually occur.
One approach is to assess whether other species are tricked similarly
to humans when presented with known illusionary phenomena (e.g.,
Murayama et al. 2012). However, as Kelley and Kelley (2014) point
out, there is great variation among species in this regard. Not only do
Behavioral Ecology
468
some human-perceived illusions not apply to other species but also
some even work in the opposite direction (e.g., Watanabe et al. 2013).
Such findings demonstrate that the rules of image perception vary
greatly across different animals, which implies that the potential “illusionary toolkit” should be correspondingly large. Rather than expecting common iterations of a limited range of illusions, we might
therefore expect many, often species-specific, examples. Intriguingly,
it follows that the true opportunity for illusion in the natural world
will greatly transcend our perception of it; that is, there are likely
countless potential routes to illusion that humans cannot even begin
to imagine. This deepens the empirical challenge because we neither
know where to look nor what to look for in the first place.
By the same token, the presence of interspecific variation in the
nature of perceptual illusions also implies great potential for signal
adaptation. Intraspecific signaling systems may evolve in ways that
elicit illusions in conspecific but not heterospecific viewers, or vice
versa. Otherwise highly conspicuous sexual ornaments may, for
example, be tuned to distort the perception of dominant predators.
Kelley and Kelley (2014) also explore how ornaments may also be
displayed in ways that selectively activate illusions, such as the displays of fiddler crabs (Callander et al. 2013) and guppies (Gasparini
et al. 2013). These examples, however, lead us back to the broader
issue of empirical estimation. Although each could signify the operation of an Ebbinghaus illusion (whereby a focal object appears
deceptively larger in comparison with smaller adjacent objects), they
are also consistent with explanations based around comparative decision making and social signaling. Heuristically, this underscores the
need to convincingly demonstrate that perceptual illusion is actually
at play. This may be accomplished through detailed knowledge of
visual and spatial processing or through linking vision and behavior in highly specific contexts. Putative motion-related illusions, for
example, such as the role of snake bands in reversing their apparent
direction of travel (Jackson et al. 1976), may be informed by knowledge of refresh rates in the eyes of relevant viewers. If we knew how
fast such a snake need ideally travel to distort the perception of its
predator(s), then this might offer a basis for testing against actual
snake movement in ecologically relevant situations. Compelling evidence may also reside in signals that match predictions for perceptual
distortion based on generalizable features, such as perspective (as in
the well-described bower bird example; e.g. Endler et al. 2010).
Overall, Kelley and Kelley (2014) present an impressive insight
into the varied potential for perceptual illusion in visual signal evolution. The crucial next step forward demands a guiding empirical framework for testing such phenomena. Given the indelible
stamp of our own perception of what constitutes a visual illusion,
the need for objectivity in such work will perhaps prove paramount
among all the endeavors of behavioral ecology.
Address correspondence to D.J. Kemp. E-mail: [email protected].
Received 9 December 2013; revised 10 January 2014;
accepted 13 January 2014; Advance Access publication 22 March 2014.
doi:10.1093/beheco/aru012
Forum editor: Sue Healy
References
Callander S, Hayes CL, Jennions MD, Backwell PRY. 2013. Experimental
evidence that immediate neighbors affect male attractiveness. Behav
Ecol. 24:730–733.
Endler JA, Endler LC, Doerr NR. 2010. Great bowerbirds create theaters with forced perspective when seen by their audience. Curr Biol.
20:1679–1684.
Gasparini C, Serena G, Pilastro A. 2013. Do unattractive friends make you
look better? Context-dependent male mating preferences in the guppy.
Proc Biol Sci. 280:20123072.
Jackson JF, Ingram W III, Campbell HW. 1976. The dorsal pigmentation
pattern of snakes as an anti-predator strategy: a multivariate approach.
Am Nat. 110:1029–1053.
Kelley LA, Kelley JL. 2014. Animal visual illusion and confusion: the
importance of a sensory perspective. Behav Ecol. 25:450–463.
Murayama T, Usui A, Takeda E, Kato K, Maejima K. 2012. Relative size
discrimination and perception of the Ebbinghaus illusion in a bottlenose
dolphin (Tursiops truncatus). Aquat Mamm. 38:333–342.
Stoddard MC, Prum RO. 2011. How colorful are birds? Evolution of the
avian plumage color gamut. Behav Ecol. 22:1042–1052.
Watanabe S, Nakamura N, Fujita K. 2013. Bantams (Gallus gallus domesticus) also perceive a reversed Zöllner illusion. Anim Cogn. 16:109–115.
Perceptual biases and animal illusions:
a response to comments on Kelley
and Kelley
Laura A. Kelleya and Jennifer L. Kelleyb
of Psychology, University of Cambridge, Downing
Street, Cambridge CB2 3EB, UK and bCentre for Evolutionary
Biology/Neuroecology Group, School of Animal Biology, The
University of Western Australia, Stirling Highway, Crawley, Western
Australia 6009, Australia
aDepartment
Can animals create illusions? What are they used for? What can
they tell us about the evolution of signaling traits and receiver
perception? These are just some of the questions that we have
attempted to address in our recent review of animal illusions
and other forms of sensory deception (Kelley and Kelley 2014).
Although it is always potentially risky to suggest an umbrella term
such as “animal illusion” to describe signals/traits with a diverse
range of functions and perceptual mechanisms, we hope that our
review stimulates behavioral ecologists to reconsider the important
role of perception in both natural and sexual selection.
That selection might act on animal perception is not a novel suggestion, and significant advances have been made by considering
the role of the “psychological landscape” (Guilford and Dawkins
1991) in sensory bias (Ryan et al. 1990; Endler 1992), sensory traps
(Christy 1995), mimicry (Wickler 1968), and perceptual biases
(Schaefer and Ruxton 2009; Ryan and Cummings 2013). The key
question is how do animal visual illusions fit into these models of
signal evolution (Théry 2014)? This is a difficult question to answer
and is one of the reasons that we presented a continuum of examples of sensory manipulation, in addition to those that might be illusory. We hope that this general approach will kick-start the debate
as to what does and does not constitute an illusion. Nonetheless,
we suggest that animal illusions can be considered part of a broad
model that describes the importance of perceptual biases in shaping the evolution of animal traits (Ryan 2014). Illusions can exploit
perceptual biases, manipulate mechanisms of perceptual processing, and enforce errors of perception. Importantly, animal illusions
may not only enhance the efficacy of sexual signals (making illusions difficult to distinguish from comparative mate choice), but
they should also act to exploit perceptual processes in other contexts, such as natural selection.
Although there has been a recent resurgence in the field of
protective coloration and significant advances have been made
in modeling animal visual systems, the underlying processes of