J Comp Physiol A DOI 10.1007/s00359-015-0988-5
REVIEW
A review of visual perception mechanisms that regulate rapid adaptive camouflage in cuttlefish Chuan‑Chin Chiao · Charles Chubb · Roger T. Hanlon
Received: 23 August 2014 / Revised: 20 January 2015 / Accepted: 12 February 2015 © Springer-Verlag Berlin Heidelberg 2015
Abstract We review recent research on the visual mechanisms of rapid adaptive camouflage in cuttlefish. These neurophysiologically complex marine invertebrates can camouflage themselves against almost any background, yet their ability to quickly (0.5–2 s) alter their body patterns on different visual backgrounds poses a vexing challenge: how to pick the correct body pattern amongst their repertoire. The ability of cuttlefish to change appropriately requires a visual system that can rapidly assess complex visual scenes and produce the motor responses—the neurally controlled body patterns— that achieve camouflage. Using specifically designed visual backgrounds and assessing the corresponding body patterns quantitatively, we and others have uncovered several aspects of scene variation that are important in regulating cuttlefish patterning responses. These include spatial scale of background pattern, background intensity, background contrast, object edge properties, object contrast polarity, object depth, and the presence of 3D objects. Moreover, arm postures and skin papillae are also regulated visually for additional aspects C.‑C. Chiao (*) · C. Chubb · R. T. Hanlon Program in Sensory Physiology and Behavior, Marine Biological Laboratory, Woods Hole, MA, USA e-mail: [email protected] C.‑C. Chiao Department of Life Science and Institute of Systems Neuroscience, National Tsing Hua University, 101, Sec 2, Kuang‑Fu Road, Hsinchu 30013, Taiwan C. Chubb Department of Cognitive Sciences and Institute for Mathematical Behavioral Sciences, University of California at Irvine, Irvine, USA R. T. Hanlon Department of Ecology and Evolutionary Biology, Brown University, Providence, RI, USA
of concealment. By integrating these visual cues, cuttlefish are able to rapidly select appropriate body patterns for concealment throughout diverse natural environments. This sensorimotor approach of studying cuttlefish camouflage thus provides unique insights into the mechanisms of visual perception in an invertebrate image-forming eye. Keywords Cephalopod · Sensorimotor system · Dynamic camouflage · Disruptive body pattern · Sepia officinalis
Introduction Cephalopod molluscs possess soft bodies, diverse behavior, elaborate skin patterning capabilities and a sophisticated visual system that controls body patterning for communication and camouflage (Hanlon and Messenger 1996). While most animals have a fixed or slowly changing camouflage pattern (e.g., in a matter of minutes or hours in some fishes and reptiles), cephalopods have evolved a different defense tactic: they use their keen vision and sophisticated skin—with direct neural control for rapid change and fine-tuned optical diversity—to rapidly (0.5–2.0 s) adapt their body pattern, posture, and skin rugosity for appropriate camouflage against a staggering array of visual backgrounds: colorful coral reefs, temperate rock reefs, kelp forests, sand or mud plains, seagrass beds, and others.
A sensorimotor and ethological approach to study cuttlefish camouflage Testing the visual cues that drive the adjustment of body patterning and posture is possible with cephalopods because camouflage is their primary defense and these softbodied, shallow-water benthic animals are behaviorally
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driven to camouflage themselves on almost any background (Hanlon and Messenger 1988); thus both natural and artificial backgrounds can be presented to cuttlefish to observe their camouflaging response (Fig. 1). The common European cuttlefish, Sepia officinalis, is particularly suited for this research because it adapts well to laboratory environments, and it ranges widely from the North Sea to equatorial Africa, including the Mediterranean, and thus must adapt to diverse visual backgrounds. This review summarizes findings (field and laboratory) particularly over the past 10 years and is based largely on experiments from our laboratory. Cumulatively, this includes 12 separate cohorts of S. officinalis; feral eggs were collected
annually from southern England, transported to Woods Hole, and cultured in the laboratory. More than 800 cuttlefish have been tested for their visual perception capabilities. Additionally, to provide ethological perspective, we have taken more than 1,500 images of camouflaged S. officinalis during field studies we have conducted in the northeast Atlantic Ocean (Vigo, Spain) and in the western (Banyuls-sur-Mer, France) and eastern Mediterranean (Izmir, Turkey) (see sample field images in Hanlon et al. 2009, and other publications). In this respect, our approach to cuttlefish camouflage represents an ethological, field-based approach to laboratory experimentation, and helps us formulate experiments and analyze them in a broader perspective of sensory ecology.
Fig. 1 A visual sensorimotor assay for probing cuttlefish perception and subsequent dynamic camouflage. Row 1 Visual backgrounds with different size, contrast, edge characteristics, and arrangement are perceived by the cuttlefish, which quickly translates the information into a complex, highly coordinated body pattern type of uniform, mottle, or disruptive (left to right in each row of photographs). Row 2 Examples of how small sand particles elicit a uniform pattern in Sepia officinalis; slightly larger gravel particles of varying higher contrast elicit a mottle pattern; and large light and dark particles, some
with high contrast, elicit a disruptive pattern. Row 3 Simple visual stimuli—such as uniformity or small to large high-contrast checkerboards—can elicit uniform, mottle, or disruptive camouflage patterns in cuttlefish. The chief difference in the latter two backgrounds is the scale of the checker. Both the visual background and the body pattern can be quantified so that correlations can be made between visual input and motor output. Row 4 Enlarged images of the uniform, mottle, and disruptive body patterns (modified from Hanlon 2007)
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Methods for quantifying body patterns An initial assay to test rapid adaptive camouflage was developed by Marshall and Messenger (1996) and Chiao and Hanlon (2001a, b); however, detailed studies of visual perception required more refined quantification of the motor output that resulted from the sensory input in this sensorimotor system. This is akin to a visual psychophysical approach, where specifically designed visual stimuli are presented to assess the perceptual processes by quantifying the performance of a human subject. Analysis of globally expressed skin patterns Various image statistics have been used to summarize the global properties of the body patterns produced by cuttlefish. Shohet et al. (2007) adapted methods from functional imaging research to analyze the body pattern change on two different substrates. This technique enables the examination of the differential expression of skin coloration in response to two different visual inputs. Independent components analysis (ICA) (Anderson et al. 2003) and principal components analysis (PCA) (Kelman et al. 2007; Zylinski et al. 2009a, b, 2012) have both been used to extract the body pattern templates from an ensemble of body pattern images. These methods show that diverse body patterns can be approximated fairly well by linear combinations of two image templates, a coarse-grained “disruptive” template and a finer grained “mottle” template. By reducing the contrast of both of these templates to 0 in the linear combination, a “uniform” pattern can be produced. Several studies have used these two image templates to quantify the patterns produced by cuttlefish in response to different stimulus substrates (Kelman et al. 2007; Zylinski et al. 2009a, b, 2012). Specifically, this method summarizes a given pattern response by the loadings of the two templates in the pattern. A useful set of summary statistics can be obtained by taking the two-dimensional Fourier transform of the cuttlefish body pattern and extracting information reflecting the contribution of different spatial frequencies to the image of the body pattern. We developed an automated method to characterize the camouflage patterns produced by cuttlefish using this latter approach (Barbosa et al. 2008b). This method enables us to discriminate among three major body pattern types in cuttlefish, namely Uniform, Mottle, and Disruptive (Fig. 1). Uniform body patterns have little or no contrast; they can range from all light to all dark. Mottle body patterns are composed of small-to-moderate-scale light and dark patches (or mottles) distributed across the body surface. There is low-to-moderate contrast between the light and dark patches, which can vary somewhat in shape and size, yet there is usually some repetition of those
patches across the body surface. Disruptive body patterns are characterized by large-scale light and dark components of multiple shapes, orientations, scales, and contrasts (Hanlon et al. 2009). In other words, these three pattern types differ in granularity (or spatial scale). We can capture such differences by analyzing the image of the animal in six, octave-wide spatial frequency bands (Barbosa et al. 2008b; Chiao et al. 2009). From each of the band-pass-filtered images, we can also extract the total energy of the original image, which is closely related to the root-mean-square (RMS) contrast typically used to characterize the contrast of complex scenes (Bex and Makous 2002). We thus refer to these six energies as the “granularity spectrum” of the image. Based on the curve shape of this granularity spectrum, three major body pattern types (Uniform, Mottle, and Disruptive patterns) can be distinguished (Fig. 2a). Typically, the spectrum of the uniform response has low energy in all six granularity bands. The mottle pattern yields a spectrum with more energy at all bands than the uniform pattern, and this spectrum has highest energy in granularity bands 3 and 4, which are mid-scale in size. Finally, the disruptive pattern evokes a spectrum with more total energy than either the uniform or mottle pattern, and most of this energy is in the two coarsest (i.e., largest scale) granularity bands: 1 and 2. Although cuttlefish are capable of producing hybrid patterns that combine features from the three basic patterns, this represents a parsimonious solution of producing diverse body patterns in nature. Note that we and others are not yet considering color or overall brightness in this analysis—we are most concerned with pattern. Also note that we distinguish a “disruptive body pattern” from “disruptive coloration” (Stevens and Merilaita 2011), the latter being a specific visual mechanism that has not yet been proved experimentally in cephalopods or many other organisms. Analysis of locally expressed skin components In cuttlefish, the disruptive body pattern is composed of many distinctive light/dark skin components. While the global analysis of body patterns allows us to classify three basic pattern types in cuttlefish, this approach does not quantify the expression of individual skin components. Thus, some feature-based image analyses are required to characterize their expression. Using a manual grading scheme, we and others have scored the activation of individual dark and light components (Kelman et al. 2008; Mäthger et al. 2006), which are independent physiological units that can be shown to operate singly or in combination with each other to form disruptive body patterns (Hanlon and Messenger 1988). By analyzing these manually scored component activations using the Principal Component Analysis (PCA),
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Fig. 2 Methods for quantifying cuttlefish body patterns. a Granularity analysis. The image of the cuttlefish is band-pass filtered into six images corresponding to those shown on the horizontal axis. From each of the six images is extracted the sum of squared pixel values; this is the total energy contributed to the original image by the spatial frequencies isolated in the filtered image. We refer to these six band-specific energies as the “granularity spectrum” of the image. The three spectra shown are typical of uniform, mottled, and disruptive patterns (modified from Barbosa et al. 2008a, b) b Component activation analysis. Activation of disruptive components can be esti-
mated from the intensity profiles along main body axes. For example, to extract the expression levels of three light and four dark skin components (WHB white head bar; WS white square; WPT white posterior triangle; AHB anterior head bar; AMB anterior mantle bar; ATML anterior transverse mantle line; PTML posterior transverse mantle line) previously identified in Sepia officinalis (Hanlon and Messenger 1988), the pixel intensity profiles along three medial lines were used to estimate their activations. Other disruptive components can be estimated from similar strategies (modified from Chiao et al. 2009)
the dimensionality can be significantly reduced and the “strength” of body patterning can be derived (Kelman et al. 2008). Although these grading methods have proven useful and are biologically accurate and relevant (Chiao et al. 2009), an automatic quantification scheme provides complementary benefits to eliminate measurement noise and potential bias in gauging the degree of activation for individual components. We have developed an automated method to quantify the activation of five light and five dark skin components responsible for disruptive body patterns in cuttlefish S. officinalis (Chiao et al. 2009). To perform this component analysis, three intensity traces are extracted from the cuttlefish image: the medial trace, the transverse mantle trace, and the transverse head trace. The medial trace (blue line, Fig. 2b, right) gives the fluctuation in image contrast ([intensity − (image mean)]/[image mean]) as a function of distance along the red lines from the topmost to the bottommost point (Fig. 2b, left). Similarly, the transverse mantle and transverse head traces give the fluctuation in image intensity across mantle and head (not shown). Seven statistics derived from the medial trace are used to estimate the activation strengths of three light components and four dark components (Fig. 2b). The other three components are derived from the two transverse traces. An overall summary statistic reflecting strength of disruptive responding is then derived from the 10 component activation strengths of each cuttlefish. The aim of this summary statistic is to approximate the manual scoring method used in our previous work.
Overall, the correlation between manual scores and predicted scores based on this automatic method is very high (Chiao et al. 2009). A similar approach has been adopted to quantify an additional three dark components on the head region (Chiao et al. 2013).
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The eye as a sensor of diverse visual backgrounds Which properties of the background determine whether a cuttlefish will produce a uniform, mottle, or disruptive pattern? This issue has received much attention over the past decade and is central to our understanding of visual perception mechanisms that regulate rapid adaptive camouflage in cuttlefish. The exceptionally fast change (ca. 1 s) implies that the visual system must extract key background features efficiently for pattern selection and pattern generation. Spatial scale Our earliest work using checkerboard backgrounds demonstrated that check sizes similar to the size of the white square (WS—a salient skin component on the cuttlefish mantle with an area approximately 10 % of the overall size of the animal; see Fig. 1) evoke disruptive body patterns (Chiao and Hanlon 2001a). In subsequent experiments, we and others established that check sizes roughly 40–120 % of WS area can also evoke disruptive body patterns, while smaller check sizes near 4–12 % of WS area are likely to
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elicit mottle patterns, and larger check sizes around 400– 1200 % of WS area make most animals express uniform body patterns (Barbosa et al. 2007, 2008b; Kelman et al. 2007, 2008; Mäthger et al. 2006; Zylinski et al. 2009a). These results suggest that body patterning of cuttlefish is scale dependent. However, checkerboards are a very restricted class of images. Moreover, checkerboards might well be a special class for cuttlefish, given that the primary constituent elements of checkerboards (square checks) resemble the form of the single most salient disruptive skin component in the S. officinalis repertoire: the white square in the middle of its dorsum. In a follow-up study, we tested whether the scale dependency of the cuttlefish patterning responses previously observed with checkerboards can be generalized to other substrates. We created random background textures differing in scale but identical in all other respects (Fig. 3). These texture substrates were derived by
filtering white noise patterns into isotropic, octave-wide frequency bands and thresholding at zero to yield binary patterns with equal proportions of black and white pixels. In general, our results support the concept that the cuttlefish patterning responses depend on substrate spatial scale (Fig. 3).
Fig. 3 Spatial scale of substrate texture affects body patterning in cuttlefish. Animals showed a transition from uniform and mottle patterns to disruptive patterns as the substrate scale increases. However,
cuttlefish did not return to uniform patterns on the last few textures (S7–S9); rather they only showed weakened disruptive body patterning (modified from Chiao et al. 2009)
Background intensity It is typically assumed that variations in Weber contrast within a scene are more important in controlling behavior than the mean luminance of the scene; however, our results demonstrate that with other factors equal, substrates with lower mean luminance tend to evoke stronger disruptive responses (Fig. 4). This was revealed clearly by Chiao et al. (2007) who devised two substrates that comprised a regular array of light squares on a dark background in which
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Fig. 4 Background intensity regulates body patterning in cuttlefish. a–b Cuttlefish showed decreasing grades of disruptive body patterns on substrates composed of large light squares (100 %-WS-size) on dark backgrounds, in which mean intensity was steadily increasing and contrast was kept relatively constant. On the upper-left corner of each image panel, absolute intensity of each patch and the Weber contrast of the brightest patch are indicated. c Averaged disruptive scores of six cuttlefish on two substrates are significantly different
(p = 0.0364), and bars represent the standard errors. MI mean intensity; WC light-square Weber contrast. d–e Cuttlefish showed similarly decreasing grades of disruptive body patterns on substrates composed of medium light squares (12 %-WS-size) on dark backgrounds (with mean intensity and contrast varied as in a and b). f Averaged disruptive scores of six cuttlefish on two substrates are significantly different (p = 0.0129) (modified from Chiao et al. 2007)
the light squares subsumed 25 % of the area, and each light square was roughly equal in size to the white squares of the cuttlefish being tested. However, one substrate was darker than the other. In the darker substrate, the light squares had reflectance 0.43 and the background had reflectance 0.14, whereas in the lighter substrate, the light squares had reflectance 0.7 and the background had reflectance 0.21. Thus, the Weber contrasts of the squares in the darker and lighter substrates were 1.02 and 1.11, respectively. Despite the fact that its squares actually had slightly lower Weber contrast, the overall darker substrate evoked a significantly larger disruptive patterning response than the lighter substrate (Fig. 4c). A test using analogous substrates with squares scaled down in size by a factor of nine yielded an analogous result: the darker substrate evoked a significantly larger disruptive response than the lighter substrate (Fig. 4f). Thus, in cuttlefish, low background intensity tends to evoke stronger disruptive patterns.
However, other aspects of the animal’s pattern are likely to change as the contrast of a fixed-patterned background is manipulated. For example, when the contrasts of checkerboard backgrounds of different sizes were varied, on high-contrast checkerboards, cuttlefish body patterning depended on check size as described above, whereas on low-contrast checkerboards—irrespective of check size— cuttlefish showed low-contrast uniform/stipple patterns (Fig. 5) (Barbosa et al. 2008b; Zylinski et al. 2009a). As substrate contrast increased, so did the contrast of the animals’ body patterns, until at high contrast, full expression of either mottle or disruptive patterns was observed (Chiao et al. 2010). One might expect such changes in body patterning with increasing background contrast because visual predators are highly sensitive to differences in contrast. Effective camouflage for a benthic organism such as cuttlefish must deceive predators viewing from above as well as from the side; thus the choice of camouflage body pattern is expected to be sensitive to visible variations both in the ground plane (i.e., the horizontal substrate) and also perpendicular to the ground plane (i.e., vertical aspects of the visual background). Most experiments have dealt only with the former. When high-contrast background patterns
Background contrast Generally the response patterns produced by a cuttlefish tend to resemble the contrast of the benthic background.
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J Comp Physiol A Fig. 5 Contrast and check size influence body patterning in cuttlefish. For high-contrast levels, body patterning depends on check size, while for lowcontrast levels, body patterning is independent of check size. Disruptive coloration was shown on 40 % check area with highest contrasts. Uniform was elicited on all check areas for the lowest contrast levels. Mottle patterning was shown on the 10 and 3 % check areas for contrast values higher than 0.34 and 0.53, respectively (modified from Barbosa et al. 2008a)
were presented on the walls of the test arena, cuttlefish also emitted disruptive body patterns (Barbosa et al. 2008a). However, there were differences in the expression of disruptive pattern components if the checkerboard was presented simultaneously on the bottom and wall, or solely on the wall or the bottom. These results demonstrate that cuttlefish respond to visual background contrast variations both in the ground plane and also perpendicular to the ground plane (see 3D visual cues below). Since contrast of the background environment is crucial in determining cuttlefish body pattern, we applied this sensory rule to show that cuttlefish body patterns depend on the luminance contrast, not the chromatic contrast, of the substrates, supporting the finding that cuttlefish are color blind (Mäthger et al. 2006). This result is consistent with an earlier finding that cuttlefish change body patterns based on the contrast—not the color—of mixed gravels (Marshall and Messenger 1996). These studies emphasize
the importance of background contrast on cuttlefish body patterning. Object edges The edge of an object is an abrupt change in spatial properties between object and background, and it is known that the visual systems of many animals are highly sensitive to edges (Troscianko et al. 2009). However, complete edges of objects are rare in cluttered visual environments. Instead, edge segments (lines and corners) are more abundant in complex backgrounds. Thus, visual sensing of salient edges/lines in the background provides cuttlefish with rich information that can be potentially used to control disruptive body pattern expression. We and others have shown that cuttlefish body patterns are influenced strongly by visual edges in the substrate (Chiao et al. 2005; Zylinski et al. 2009b). In a recent study,
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Fig. 6 Continuous edges and line terminators influence expression of disruptive body pattern components via different mechanisms that are controlled by contrast in different ways. A gray field populated with randomly placed white disks was filtered into a high spatial frequency band to produce low-contrast full-edge rings (S3). Low-contrast, quarter-edge rings (S4) were produced by erasing a random 270 deg arc from each low-contrast full-edge-ring. High-contrast versions of these edge substrates were generated by maximizing the overall contrast (S5 and S6). High-contrast edge fragments evoked substantially stronger body pattern responses than low-contrast edge fragments, whereas the body pattern responses evoked by high-contrast continuous edges were no stronger than those produced by low-contrast edges (modified from Chiao et al. 2013)
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choice of body patterns. An almost entirely homogeneous dark background that contains even a single white element of roughly the same area as the white square of the cuttlefish will evoke a disruptive body pattern (Chiao and Hanlon 2001a). This effect is specific to light objects; dark elements on the same background (with equal contrast to the background as the white elements) fail to evoke disruptive body patterns (Mäthger et al. 2007; Kelman et al. 2008). This response to sparse white background elements is surprisingly invariant with respect to their shapes (Chiao and Hanlon 2001b) or the size and age of the cuttlefish (Barbosa et al. 2007). In a recent study (Chiao et al. 2013), however, we found that although disks of both contrast polarities evoked relatively weak disruptive body patterns, black disks activated different skin components than white disks, and high-frequency information alone sufficed to drive the responses to white disks whereas high- and low-frequency information were both required to drive responses to black disks (Fig. 5 in Chiao et al. 2013). Thus, the patterning response is sensitive to the contrast polarity of the substrate; that is, the skin components activated by the substrate comprising black disks on a gray background tend to be dark, whereas those activated by white disks on a gray background tend to be light. This finding supports the concept that object contrast polarity plays a role in determining a cuttlefish’s body pattern type. Object depth and 3D
we systematically examined how cuttlefish body patterning is differentially controlled by various aspects of edges (Chiao et al. 2013). Strikingly, we found that high-contrast edge fragments (including abrupt points of termination) evoked substantially stronger body pattern responses than low-contrast edge fragments, whereas the body pattern responses evoked by high-contrast closed edges (i.e., circles without points of termination) were no stronger than those produced by low-contrast edges (Fig. 6). This suggests that line terminators vs. continuous edges influence expression of disruptive body pattern components via different mechanisms that are controlled by contrast in different ways. In addition, a recent study shows that cuttlefish respond to circles fragmented by gaps differently than they do to randomly scattered circle fragments (Zylinski et al. 2012). This suggests that cuttlefish are sensitive to the colinearity of the components in the circles fragmented by gaps.
Visual depth (both real and pictorial depth) appears to be one key in evoking disruptive patterns (Kelman et al. 2008). We also investigated the role of an isolated threedimensional object vs a continuous background substrate in controlling the patterning responses produced by cuttlefish (Buresch et al. 2011). We found that the three-dimensional object exerted a strong influence on patterning responses only if the object was marked by a high-contrast pattern (Fig. 7). In this case, cuttlefish showed a strong tendency to take their sensory cues from the pattern of the object. However, uniform gray objects exerted no measurable influence on responding. Thus, contrast of 3D objects is an important visual cue for masquerade (i.e., looking like another object rather than resembling the substrate; Stevens and Merilaita 2011). This study also supports the important role of object contrast as a cue in the cuttlefish’s preference to resemble 3D objects rather than the benthic substrate. Regulation of 3D physical skin texture and arm posture
Object contrast polarity The presence of white (or light) elements on the dark background is an important factor regulating a cuttlefish’s
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Cephalopods are unique in the animal kingdom for having neurally controlled muscular papillae in the skin to quickly change the shape of their skin from smooth to
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Fig. 7 Presence of 3D objects modulates body patterning in cuttlefish. Animals were tested for a preference to show a body pattern appropriate for the 3D object or the benthic substrate. Cuttlefish
responded by masquerading as the 3D object, rather than resembling the benthic substrate, only when presented with a high-contrast object on a substrate of lower contrast (modified from Buresch et al. 2011)
highly rugose; i.e., from flat 2D to papillate 3D. Allen et al. (2009) conducted experiments to determine whether S. officinalis use tactile or visual cues to control papillae expression (because hypothetically they could acquire tactile information from the suckers on their arms). Cuttlefish were placed on natural substrates to evoke the three major camouflage body patterns: Uniform, Mottle and Disruptive. Three versions of each substrate were presented: the actual substrate, the actual substrate covered with glass (removes tactile information) and a laminated photograph of the substrate (removes tactile and three-dimensional information because depth-of-field information is unavailable). No differences in papillae expression were observed among the three versions of each substrate; thus visual (not tactile) cues drive the expression of papillae. However, there were no tests to determine which visual background cues were eliciting papillae expression. Similarly, cuttlefish deploy some of their arms (they have 8) upwards and sideways when they are camouflaging themselves adjacent to vertical objects that have relatively thin protrusions (e.g., branches of a soft coral or alga) to enhance their camouflage via body posture. Barbosa et al. (2012) demonstrated experimentally that S. officinalis adjust the orientation of their raised arms to align with the orientation of stripes on a wall (horizontal, 45°, and 90°); when there were no stripes, the cuttlefish did not raise their arms at all (Fig. 8). In these experiments, the visual stimuli were high-contrast (black and white) stripes, each the width of the animals’ arms. Field photographs and video confirm these results from the laboratory. Collectively, these studies show that the eyes are sensing the vertical orientation of adjacent objects to guide arm postures, and are also able to sense the fine 3D texture of adjacent backgrounds and generally replicate that in their skin.
Scene analysis and feature integration for rapid camouflage body patterning How does a cuttlefish so quickly analyze the scene and put on an appropriate body pattern to conceal itself within a given background? Part of the answer lies, we believe, in the counterintuitive finding that cuttlefish appear to have evolved only 3 basic pattern templates (Uniform, Mottle, Disruptive, each with variation) with which to achieve concealment (e.g., Hanlon 2007). Thus, one working hypothesis is that the pattern deployed by a cuttlefish in response to a particular visual background reflects a two-stage process in which a relatively simple set of “visual sampling rules” is first used to select one of the three basic pattern types, which is then further refined in a second stage of processing that depends on subtler statistical features of the background. A somewhat comparable idea has been proposed by Zylinski et al. (2009a), in which a simple model focusing on cuttlefish edge detection is used to determine pattern types, then finer control of skin coloration is modulated by other substrate features. In any case, it is the remarkable speed of change (including orchestration of 2–3 million chromatophore organs in the skin) that suggests some sort of refined parsimonious visual sensing/perception process. It is apparent that multiple visual features including spatial scale, background intensity, background contrast, object edges, object contrast polarity, object depth, presence of 3D objects, etc., are important cues for cuttlefish to achieve effective camouflage (Hanlon 2007; Hanlon et al. 2011; Zylinski and Osorio 2011; Zylinski et al. 2009b). We can think of the eye as a sensor of diverse visual backgrounds, and cuttlefish acquire visual information by actively sensing surrounding environments with vertebratelike eyes (Packard 1972; Messenger 1991). The detailed
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Fig. 8 Cuttlefish adjust their arm postures visually according to the orientation of stripes on the wall of the aquarium, thus enhancing camouflage via posture. Field images show cuttlefish raising arm pos-
tures similarly when settled next to vertically oriented algae and corals (modified from Barbosa et al. 2012)
structure and functions of the cuttlefish eye are rather peculiar, however: a W-shaped pupil, polarization sensitivity, no color vision, good visual acuity, and good night vision. Significant visual processing that extracts multiple visual features of substrates occurs in the optic lobe, the largest brain area in cephalopods. The parallel nature of this visual information processing is somewhat akin to human vision (Zylinski and Osorio 2011). However, little is known about feature integration in the cuttlefish brain and the resultant motor act that produces the body pattern for camouflage. Earlier studies have shown that stimulating the optic lobe alone with extracellular electrodes generates whole body pattern changes (Boycott 1961; Chichery and Chanelet 1976). Thus, it is likely that the optic lobe is the neural substrate in which cuttlefish integrate these visual features and determine the appropriate body pattern types for camouflage. After the stage of pattern selection (action planning), various skin components—which are controlled by physiological units in the brain innervating motor fields on the skin (Packard 1982)—are activated selectively to generate body patterns. This processing stage is probably under the neural control of the lateral basal lobes (intermediary motor centers) and chromatophore lobes (lower motor centers) (Messenger 2001). Motor neurons in the chromatophore lobes extend directly (without synapse) to chromatophore organs throughout the skin. Thus, the coordinated neural signals from a hierarchy in the brain excite radial muscles controlling the expansion of chromatophore organs in the
skin and generate appropriate body patterns for camouflage. Additionally, neural signals excite muscular hydrostats that erect skin papillae as well as arm muscles to position the arms for postural camouflage. The entire process (minus papillae and arm postures) is summarized in Fig. 9, which illustrates our current representation of visual perception and motor control mechanisms that regulate rapid adaptive camouflage in the cuttlefish S. officinalis. There are several marine fishes capable of rapid adaptive camouflage but practically no research on the visual perception that guides pattern choice. With winter and summer flounder, Saidel (1988) concluded that both mean reflectance and contrast of the background have an influence on body pattern. Ramachandran et al. (1996) found that the tropical flounder Bothus ocellatus had three basic camouflage patterns that responded to checkerboards, sand, and gravel but performed no experiments to probe visual perception of the fish. Kelman et al. (2006) found two basic body patterns under active control in plaice (Pleuronectes platessa) but did not address the visual perception of the fish. Tyrie et al. (2015), in a field study of the coral reef flounder Bothus lunatus, found two pattern types (uniform and mottle) that the fishes chose to deploy after selecting certain substrates and avoiding others. Here, the eyes were not only using surrounding benthic visual information to decide on uniform or mottle patterns, but were using visual input to select certain substrates over others.
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Fig. 9 A schematic representation of neural processing stages in cuttlefish camouflage behavior. Cuttlefish acquire visual information by actively sensing surrounding environments with vertebrate-like eyes (visual input). Significant information processing then takes place in the optic lobe to extract multiple visual features of substrates (visual processing). Essential visual cues known to affect cuttlefish camouflage include spatial scale, background intensity, background contrast, object edges, object contrast polarity, and object depth, etc. Cuttlefish then integrate all of these visual features and determine the appro-
priate body pattern types for camouflage, presumably in the optic lobe (pattern selection). To generate the selected body pattern, various skin components responsible for the composition of these body pattern types are selectively activated, perhaps under neural control in the lateral basal lobes and the chromatophore lobes (pattern generation). Finally, the coordinated neural signals from the brain excite radial muscles controlling the expansion of chromatophore organs on the skin and generate appropriate body coloration and patterning for camouflage (motor output)
Conclusion and future research
known in some detail (the subject of this review), but the mechanisms that control the fine tuning of each of these pattern types have barely been studied. Continued detailed psychophysical studies such as those by Zylinski et al. (2009a, 2012) and Chiao et al. (2013) are warranted in this respect. In addition, assessing body patterning on more natural and complex backgrounds (similar to Allen et al. 2010; Mäthger et al. 2007) is likely to shed light in understanding the interplays of these basic features in eliciting body pattern types. Another potentially fruitful approach seeks to analyze the dynamics of cuttlefish patterning responses by presenting stimulus substrate patterns whose properties are varied in real time, in ways that depend on the response patterns they elicit. This approach will most likely require special display technology that reflects ambient light rather than creates light; cuttlefish react poorly to displays that emit light. Moreover, Liquid Crystal Display monitors are not suitable because cuttlefish are highly sensitive to the variations in light polarization that are used to produce different intensities in such displays. However, display
Cephalopods combine keen visual sensing of backgrounds with neurally controlled skin patterning to achieve rapid adaptive camouflage patterns that are linked inextricably to camouflage behavior. It takes large segments of a complex nervous system to coordinate these patterns, which may partly explain why most other animals have not evolved such diverse adaptive camouflage. In this respect, it would be rewarding to study the visual perception mechanisms of the few marine teleost fishes that change camouflage rapidly. The effectiveness of the patterning strategies used by cuttlefish in eluding detection suggests that analysis of these strategies can provide key insights into the visual processes of predators (e.g., texture segregation, edge extraction, and object recognition). Many avenues of future research promise to deepen our understanding of this visual sensorimotor system. In general, the basic features that stimulate deployment of the main pattern types (Uniform, Mottle, Disruptive) are
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technologies that solely reflect light without a polarization signature (such as cholesteric displays) offer a promising option. Many open questions remain concerning cuttlefish physiology. For example, how do cephalopods accomplish color-blind camouflage? Cuttlefish color resemblance to backgrounds in nature appears to be very good (e.g., Hanlon et al. 2013) yet they are color blind (Marshall and Messenger 1996; Mäthger et al. 2006). Opsin molecules in the skin may provide some form of light sensing that affects body patterns (Mäthger et al. 2010) although they may not be for color matching. As for processing of visual information, practically nothing is yet known about the level of this in the retina of S. officinalis, except some recent studies on cephalopod eyes that revealed their contrast sensitivity and spatial resolution (Mäthger et al. 2013; Nilsson et al. 2013; Chung and Marshall 2014). Although there is basic information on the gross anatomy of the optic lobes of Octopus and the squid Loligo (Young 1962, 1974), the fine connections and the physiology remain unstudied. The functional roles of the other brain centers involved in body patterning expression (particularly the lateral basal and chromatophore lobes) remain mostly unstudied in Sepia although there are various studies of these lobes in other cephalopods (summarized in Messenger 2001). The processes controlling peripheral innervation and activation of the pigmented chromatophore organs and the structural coloration cells (iridophores) are poorly understood (Messenger 2001; Gonzalez-Bellido et al. 2014; Tublitz et al. 2006). Challenges to the hypothesized scenario projected in Fig. 9 are welcomed, particularly papers that are experimental in design.
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J Comp Physiol A substrate contrast and size in evoking uniform, mottle or disruptive body patterns. Vision Res 48:1242–1253 Barbosa A, Allen JJ, Mäthger LM, Hanlon RT (2012) Cuttlefish use visual cues to determine arm postures for camouflage. Proc Biol Sci 279:84–90 Bex PJ, Makous W (2002) Spatial frequency, phase, and the contrast of natural images. J Opt Soc Am A: 19:1096–1106 Boycott BB (1961) The functional organization of the brain of the cuttlefish Sepia officinalis. Proc R Soc Lond B 153:503–534 Buresch KC, Mathger LM, Allen JJ, Bennice C, Smith N, Schram J, Chiao C-C, Chubb C, Hanlon RT (2011) The use of background matching vs. masquerade for camouflage in cuttlefish Sepia officinalis. Vision Res 51:2362–2368 Chiao C-C, Hanlon RT (2001a) Cuttlefish camouflage: visual perception of size, contrast and number of white squares on artificial checkerboard substrata initiates disruptive coloration. J Exp Biol 204:2119–2125 Chiao C-C, Hanlon RT (2001b) Cuttlefish cue visually on area - not shape or aspect ratio - of light objects in the substrate to produce disruptive body patterns for camouflage. Biol Bull 201:269–270 Chiao C-C, Kelman EJ, Hanlon RT (2005) Disruptive body patterning of cuttlefish (Sepia officinalis) requires visual information regarding edges and contrast of objects in natural substrate backgrounds. Biol Bull 208:7–11 Chiao C-C, Chubb C, Hanlon RT (2007) Interactive effects of size, contrast, intensity and configuration of background objects in evoking disruptive camouflage in cuttlefish. Vision Res 47:2223–2235 Chiao C-C, Chubb C, Buresch K, Siemann L, Hanlon RT (2009) The scaling effects of substrate texture on camouflage patterning in cuttlefish. Vision Res 49:1647–1656 Chiao C-C, Chubb C, Buresch KC, Barbosa A, Allen JJ, Mäthger LM, Hanlon RT (2010) Mottle camouflage patterns in cuttlefish: quantitative characterization and visual background stimuli that evoke them. J Exp Biol 213:187–199 Chiao C-C, Ulmer KM, Siemann LA, Buresch KC, Chubb C, Hanlon RT (2013) How visual edge features influence cuttlefish camouflage patterning. Vision Res 83:40–47 Chichery R, Chanelet J (1976) Motor and behavioral responses obtained by stimulation with chronic electrodes of the optic lobe of Sepia officinalis. Brain Res 105:525–532 Chung WS, Marshall NJ (2014) Range-finding in squid using retinal deformation and image blur. Curr Biol 24:R64–R65 Gonzalez-Bellido PT, Wardill TJ, Buresch KC, Ulmer KM, Hanlon RT (2014) Expression of squid iridescence depends on environmental luminance and peripheral ganglion control. J Exp Biol 217:850–858 Hanlon RH (2007) Cephalopod dynamic camouflage. Curr Biol 17:R400–R404 Hanlon RT, Messenger JB (1988) Adaptive coloration in young cuttlefish (Sepia officinalis L.): The morphology and development of body patterns and their relation to behaviour. Philos Trans R Soc Lond B 320:437–487 Hanlon RT, Messenger JB (1996) Cephalopod Behaviour. Cambridge University Press, Cambridge Hanlon RT, Chiao C-C, Mäthger LM, Barbosa A, Buresch KC, Chubb C (2009) Cephalopod dynamic camouflage: bridging the continuum between background matching and disruptive coloration. Philos Trans R Soc Lond B Biol Sci 364:429–437 Hanlon RT, Chiao C-C, Mäthger LM, Buresch KC, Barbosa A, Allen JJ, Siemann L, Chubb C (2011) Rapid adaptive camouflage in cephalopods. In: Stevens M, Merilaita S (eds) Animal camouflage: mechanisms and functions. Cambridge University Press, Cambridge, U.K. Hanlon RT, Chiao C-C, Mathger LM, Marshall NJ (2013) A fish-eye view of cuttlefish camouflage using in situ spectrometry. Biol J Linn Soc 109:535–551
J Comp Physiol A Kelman EJ, Tiptus P, Osorio D (2006) Juvenile plaice (Pleuronectes platessa) produce camouflage by flexibly combining two separate patterns. J Exp Biol 209:3288–3292 Kelman EJ, Baddeley RJ, Shohet AJ, Osorio D (2007) Perception of visual texture and the expression of disruptive camouflage by the cuttlefish, Sepia officinalis. Proc Biol Sci 274:1369–1375 Kelman EJ, Osorio D, Baddeley RJ (2008) A review of cuttlefish camouflage and object recognition and evidence for depth perception. J Exp Biol 211:1163–1757 Marshall NJ, Messenger JB (1996) Colour-blind camouflage. Nature 382:408–409 Mäthger LM, Barbosa A, Miner S, Hanlon RT (2006) Color blindness and contrast perception in cuttlefish (Sepia officinalis) determined by a visual sensorimotor assay. Vision Res 46:1746–1753 Mäthger LM, Chiao C-C, Barbosa A, Buresch KC, Kaye S, Hanlon RT (2007) Disruptive coloration elicited on controlled natural substrates in cuttlefish, Sepia officinalis. J Exp Biol 210:2657–2666 Mäthger LM, Roberts SB, Hanlon RT (2010) Evidence for distributed light sensing in the skin of cuttlefish, Sepia officinalis. Biol Lett 6:600–603 Mäthger LM, Hanlon RT, Hakansson J, Nilsson DE (2013) The W-shaped pupil in cuttlefish (Sepia officinalis): functions for improving horizontal vision. Vision Res 83:19–24. doi:10.1016/j. visres.2013.02.016 Messenger JB (1991) Photoreception and vision in molluscs. In: Cronly-Dillon JR, Gregory RL (eds) Vision and visual dysfunction, vol 2., Evolution of the eye and visual systemMacmillan Press, London, pp 364–397 Messenger JB (2001) Cephalopod chromatophores: Neurobiology and natural history. Biol Rev 76:473–528 Nilsson DE, Warrant EJ, Johnsen S, Hanlon RT, Shashar N (2013) The giant eyes of giant squid are indeed unexpectedly large, but not if used for spotting sperm whales. BMC Evol Biol 13:187 Packard A (1972) Cephalopods and fish: the limits of convergence. Biol Rev 47:241–307 Packard A (1982) Morphogenesis of chromatophore patterns in cephalopods: Are morphological and physiological ‘units’ the same? Malacologia 23:193–201
Ramachandran VS, Tyler CW, Gregory RL, Rogers-Ramachandran D, Duensing S, Pillsbury C, Ramachandran C (1996) Rapid adaptive camouflage in tropical flounders. Nature 379(6568):815–818 Saidel WM (1988) How to be unseen: An essay in obscurity. In: Fay RR, Popper AN, Tavolga WN (eds) Atema J. Sensory Biology of Aquatic Animals Springer-Verlag, New York, pp 487–513 Shohet A, Baddeley R, Anderson J, Osorio D (2007) Cuttlefish camouflage: a quantitative study of patterning. Biol J Linn Soc 92:335–345 Stevens M, Merilaita S (2011) Animal Camouflage: Mechanisms and Function. Cambridge University Press, Cambridge Troscianko T, Benton CP, Lovell PG, Tolhurst DJ, Pizlo Z (2009) Camouflage and visual perception. Philos Trans R Soc Lond B 364:449–461 Tublitz NJ, Gaston MR, Loi PK (2006) Neural regulation of a complex behavior: body patterning in cephalopod molluscs. Integr Comp Biol 46:880–889 Tyrie EK, Hanlon RT, Siemann L, Uyarra MC (2015) Coral reef flounders, Bothus lunatus, choose substrates on which they can achieve camouflage with their limited body pattern repertoire. Biol J Linn Soc (in press) Young JZ (1962) The optic lobes of Octopus vulgaris. Philos Trans R Soc Lond B 245:19–58 Young JZ (1974) The central nervous system of Loligo. I. The optic lobe. Philos Trans R Soc Lond B 267:263–302 Zylinski S, Osorio D (2011) What can camouflage tell us about nonhuman visual perception? A case study of multiple cue use in the cuttlefish. In: Stevens M, Merilaita S (eds) Animal camouflage: mechanisms and functions. Cambridge University Press, Cambridge, U.K. Zylinski S, Osorio D, Shohet AJ (2009a) Edge detection and texture classification by cuttlefish. J Vision 9:1–10 Zylinski S, Osorio D, Shohet AJ (2009b) Perception of edges and visual texture in the camouflage of the common cuttlefish, Sepia officinalis. Philos Trans R Soc Lond B 364:439–448 Zylinski S, Darmaillacq AS, Shashar N (2012) Visual interpolation for contour completion by the European cuttlefish (Sepia officinalis) and its use in dynamic camouflage. Proc Biol Sci 279:2386–2390
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REVIEW
A review of visual perception mechanisms that regulate rapid adaptive camouflage in cuttlefish Chuan‑Chin Chiao · Charles Chubb · Roger T. Hanlon
Received: 23 August 2014 / Revised: 20 January 2015 / Accepted: 12 February 2015 © Springer-Verlag Berlin Heidelberg 2015
Abstract We review recent research on the visual mechanisms of rapid adaptive camouflage in cuttlefish. These neurophysiologically complex marine invertebrates can camouflage themselves against almost any background, yet their ability to quickly (0.5–2 s) alter their body patterns on different visual backgrounds poses a vexing challenge: how to pick the correct body pattern amongst their repertoire. The ability of cuttlefish to change appropriately requires a visual system that can rapidly assess complex visual scenes and produce the motor responses—the neurally controlled body patterns— that achieve camouflage. Using specifically designed visual backgrounds and assessing the corresponding body patterns quantitatively, we and others have uncovered several aspects of scene variation that are important in regulating cuttlefish patterning responses. These include spatial scale of background pattern, background intensity, background contrast, object edge properties, object contrast polarity, object depth, and the presence of 3D objects. Moreover, arm postures and skin papillae are also regulated visually for additional aspects C.‑C. Chiao (*) · C. Chubb · R. T. Hanlon Program in Sensory Physiology and Behavior, Marine Biological Laboratory, Woods Hole, MA, USA e-mail: [email protected] C.‑C. Chiao Department of Life Science and Institute of Systems Neuroscience, National Tsing Hua University, 101, Sec 2, Kuang‑Fu Road, Hsinchu 30013, Taiwan C. Chubb Department of Cognitive Sciences and Institute for Mathematical Behavioral Sciences, University of California at Irvine, Irvine, USA R. T. Hanlon Department of Ecology and Evolutionary Biology, Brown University, Providence, RI, USA
of concealment. By integrating these visual cues, cuttlefish are able to rapidly select appropriate body patterns for concealment throughout diverse natural environments. This sensorimotor approach of studying cuttlefish camouflage thus provides unique insights into the mechanisms of visual perception in an invertebrate image-forming eye. Keywords Cephalopod · Sensorimotor system · Dynamic camouflage · Disruptive body pattern · Sepia officinalis
Introduction Cephalopod molluscs possess soft bodies, diverse behavior, elaborate skin patterning capabilities and a sophisticated visual system that controls body patterning for communication and camouflage (Hanlon and Messenger 1996). While most animals have a fixed or slowly changing camouflage pattern (e.g., in a matter of minutes or hours in some fishes and reptiles), cephalopods have evolved a different defense tactic: they use their keen vision and sophisticated skin—with direct neural control for rapid change and fine-tuned optical diversity—to rapidly (0.5–2.0 s) adapt their body pattern, posture, and skin rugosity for appropriate camouflage against a staggering array of visual backgrounds: colorful coral reefs, temperate rock reefs, kelp forests, sand or mud plains, seagrass beds, and others.
A sensorimotor and ethological approach to study cuttlefish camouflage Testing the visual cues that drive the adjustment of body patterning and posture is possible with cephalopods because camouflage is their primary defense and these softbodied, shallow-water benthic animals are behaviorally
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driven to camouflage themselves on almost any background (Hanlon and Messenger 1988); thus both natural and artificial backgrounds can be presented to cuttlefish to observe their camouflaging response (Fig. 1). The common European cuttlefish, Sepia officinalis, is particularly suited for this research because it adapts well to laboratory environments, and it ranges widely from the North Sea to equatorial Africa, including the Mediterranean, and thus must adapt to diverse visual backgrounds. This review summarizes findings (field and laboratory) particularly over the past 10 years and is based largely on experiments from our laboratory. Cumulatively, this includes 12 separate cohorts of S. officinalis; feral eggs were collected
annually from southern England, transported to Woods Hole, and cultured in the laboratory. More than 800 cuttlefish have been tested for their visual perception capabilities. Additionally, to provide ethological perspective, we have taken more than 1,500 images of camouflaged S. officinalis during field studies we have conducted in the northeast Atlantic Ocean (Vigo, Spain) and in the western (Banyuls-sur-Mer, France) and eastern Mediterranean (Izmir, Turkey) (see sample field images in Hanlon et al. 2009, and other publications). In this respect, our approach to cuttlefish camouflage represents an ethological, field-based approach to laboratory experimentation, and helps us formulate experiments and analyze them in a broader perspective of sensory ecology.
Fig. 1 A visual sensorimotor assay for probing cuttlefish perception and subsequent dynamic camouflage. Row 1 Visual backgrounds with different size, contrast, edge characteristics, and arrangement are perceived by the cuttlefish, which quickly translates the information into a complex, highly coordinated body pattern type of uniform, mottle, or disruptive (left to right in each row of photographs). Row 2 Examples of how small sand particles elicit a uniform pattern in Sepia officinalis; slightly larger gravel particles of varying higher contrast elicit a mottle pattern; and large light and dark particles, some
with high contrast, elicit a disruptive pattern. Row 3 Simple visual stimuli—such as uniformity or small to large high-contrast checkerboards—can elicit uniform, mottle, or disruptive camouflage patterns in cuttlefish. The chief difference in the latter two backgrounds is the scale of the checker. Both the visual background and the body pattern can be quantified so that correlations can be made between visual input and motor output. Row 4 Enlarged images of the uniform, mottle, and disruptive body patterns (modified from Hanlon 2007)
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Methods for quantifying body patterns An initial assay to test rapid adaptive camouflage was developed by Marshall and Messenger (1996) and Chiao and Hanlon (2001a, b); however, detailed studies of visual perception required more refined quantification of the motor output that resulted from the sensory input in this sensorimotor system. This is akin to a visual psychophysical approach, where specifically designed visual stimuli are presented to assess the perceptual processes by quantifying the performance of a human subject. Analysis of globally expressed skin patterns Various image statistics have been used to summarize the global properties of the body patterns produced by cuttlefish. Shohet et al. (2007) adapted methods from functional imaging research to analyze the body pattern change on two different substrates. This technique enables the examination of the differential expression of skin coloration in response to two different visual inputs. Independent components analysis (ICA) (Anderson et al. 2003) and principal components analysis (PCA) (Kelman et al. 2007; Zylinski et al. 2009a, b, 2012) have both been used to extract the body pattern templates from an ensemble of body pattern images. These methods show that diverse body patterns can be approximated fairly well by linear combinations of two image templates, a coarse-grained “disruptive” template and a finer grained “mottle” template. By reducing the contrast of both of these templates to 0 in the linear combination, a “uniform” pattern can be produced. Several studies have used these two image templates to quantify the patterns produced by cuttlefish in response to different stimulus substrates (Kelman et al. 2007; Zylinski et al. 2009a, b, 2012). Specifically, this method summarizes a given pattern response by the loadings of the two templates in the pattern. A useful set of summary statistics can be obtained by taking the two-dimensional Fourier transform of the cuttlefish body pattern and extracting information reflecting the contribution of different spatial frequencies to the image of the body pattern. We developed an automated method to characterize the camouflage patterns produced by cuttlefish using this latter approach (Barbosa et al. 2008b). This method enables us to discriminate among three major body pattern types in cuttlefish, namely Uniform, Mottle, and Disruptive (Fig. 1). Uniform body patterns have little or no contrast; they can range from all light to all dark. Mottle body patterns are composed of small-to-moderate-scale light and dark patches (or mottles) distributed across the body surface. There is low-to-moderate contrast between the light and dark patches, which can vary somewhat in shape and size, yet there is usually some repetition of those
patches across the body surface. Disruptive body patterns are characterized by large-scale light and dark components of multiple shapes, orientations, scales, and contrasts (Hanlon et al. 2009). In other words, these three pattern types differ in granularity (or spatial scale). We can capture such differences by analyzing the image of the animal in six, octave-wide spatial frequency bands (Barbosa et al. 2008b; Chiao et al. 2009). From each of the band-pass-filtered images, we can also extract the total energy of the original image, which is closely related to the root-mean-square (RMS) contrast typically used to characterize the contrast of complex scenes (Bex and Makous 2002). We thus refer to these six energies as the “granularity spectrum” of the image. Based on the curve shape of this granularity spectrum, three major body pattern types (Uniform, Mottle, and Disruptive patterns) can be distinguished (Fig. 2a). Typically, the spectrum of the uniform response has low energy in all six granularity bands. The mottle pattern yields a spectrum with more energy at all bands than the uniform pattern, and this spectrum has highest energy in granularity bands 3 and 4, which are mid-scale in size. Finally, the disruptive pattern evokes a spectrum with more total energy than either the uniform or mottle pattern, and most of this energy is in the two coarsest (i.e., largest scale) granularity bands: 1 and 2. Although cuttlefish are capable of producing hybrid patterns that combine features from the three basic patterns, this represents a parsimonious solution of producing diverse body patterns in nature. Note that we and others are not yet considering color or overall brightness in this analysis—we are most concerned with pattern. Also note that we distinguish a “disruptive body pattern” from “disruptive coloration” (Stevens and Merilaita 2011), the latter being a specific visual mechanism that has not yet been proved experimentally in cephalopods or many other organisms. Analysis of locally expressed skin components In cuttlefish, the disruptive body pattern is composed of many distinctive light/dark skin components. While the global analysis of body patterns allows us to classify three basic pattern types in cuttlefish, this approach does not quantify the expression of individual skin components. Thus, some feature-based image analyses are required to characterize their expression. Using a manual grading scheme, we and others have scored the activation of individual dark and light components (Kelman et al. 2008; Mäthger et al. 2006), which are independent physiological units that can be shown to operate singly or in combination with each other to form disruptive body patterns (Hanlon and Messenger 1988). By analyzing these manually scored component activations using the Principal Component Analysis (PCA),
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Fig. 2 Methods for quantifying cuttlefish body patterns. a Granularity analysis. The image of the cuttlefish is band-pass filtered into six images corresponding to those shown on the horizontal axis. From each of the six images is extracted the sum of squared pixel values; this is the total energy contributed to the original image by the spatial frequencies isolated in the filtered image. We refer to these six band-specific energies as the “granularity spectrum” of the image. The three spectra shown are typical of uniform, mottled, and disruptive patterns (modified from Barbosa et al. 2008a, b) b Component activation analysis. Activation of disruptive components can be esti-
mated from the intensity profiles along main body axes. For example, to extract the expression levels of three light and four dark skin components (WHB white head bar; WS white square; WPT white posterior triangle; AHB anterior head bar; AMB anterior mantle bar; ATML anterior transverse mantle line; PTML posterior transverse mantle line) previously identified in Sepia officinalis (Hanlon and Messenger 1988), the pixel intensity profiles along three medial lines were used to estimate their activations. Other disruptive components can be estimated from similar strategies (modified from Chiao et al. 2009)
the dimensionality can be significantly reduced and the “strength” of body patterning can be derived (Kelman et al. 2008). Although these grading methods have proven useful and are biologically accurate and relevant (Chiao et al. 2009), an automatic quantification scheme provides complementary benefits to eliminate measurement noise and potential bias in gauging the degree of activation for individual components. We have developed an automated method to quantify the activation of five light and five dark skin components responsible for disruptive body patterns in cuttlefish S. officinalis (Chiao et al. 2009). To perform this component analysis, three intensity traces are extracted from the cuttlefish image: the medial trace, the transverse mantle trace, and the transverse head trace. The medial trace (blue line, Fig. 2b, right) gives the fluctuation in image contrast ([intensity − (image mean)]/[image mean]) as a function of distance along the red lines from the topmost to the bottommost point (Fig. 2b, left). Similarly, the transverse mantle and transverse head traces give the fluctuation in image intensity across mantle and head (not shown). Seven statistics derived from the medial trace are used to estimate the activation strengths of three light components and four dark components (Fig. 2b). The other three components are derived from the two transverse traces. An overall summary statistic reflecting strength of disruptive responding is then derived from the 10 component activation strengths of each cuttlefish. The aim of this summary statistic is to approximate the manual scoring method used in our previous work.
Overall, the correlation between manual scores and predicted scores based on this automatic method is very high (Chiao et al. 2009). A similar approach has been adopted to quantify an additional three dark components on the head region (Chiao et al. 2013).
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The eye as a sensor of diverse visual backgrounds Which properties of the background determine whether a cuttlefish will produce a uniform, mottle, or disruptive pattern? This issue has received much attention over the past decade and is central to our understanding of visual perception mechanisms that regulate rapid adaptive camouflage in cuttlefish. The exceptionally fast change (ca. 1 s) implies that the visual system must extract key background features efficiently for pattern selection and pattern generation. Spatial scale Our earliest work using checkerboard backgrounds demonstrated that check sizes similar to the size of the white square (WS—a salient skin component on the cuttlefish mantle with an area approximately 10 % of the overall size of the animal; see Fig. 1) evoke disruptive body patterns (Chiao and Hanlon 2001a). In subsequent experiments, we and others established that check sizes roughly 40–120 % of WS area can also evoke disruptive body patterns, while smaller check sizes near 4–12 % of WS area are likely to
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elicit mottle patterns, and larger check sizes around 400– 1200 % of WS area make most animals express uniform body patterns (Barbosa et al. 2007, 2008b; Kelman et al. 2007, 2008; Mäthger et al. 2006; Zylinski et al. 2009a). These results suggest that body patterning of cuttlefish is scale dependent. However, checkerboards are a very restricted class of images. Moreover, checkerboards might well be a special class for cuttlefish, given that the primary constituent elements of checkerboards (square checks) resemble the form of the single most salient disruptive skin component in the S. officinalis repertoire: the white square in the middle of its dorsum. In a follow-up study, we tested whether the scale dependency of the cuttlefish patterning responses previously observed with checkerboards can be generalized to other substrates. We created random background textures differing in scale but identical in all other respects (Fig. 3). These texture substrates were derived by
filtering white noise patterns into isotropic, octave-wide frequency bands and thresholding at zero to yield binary patterns with equal proportions of black and white pixels. In general, our results support the concept that the cuttlefish patterning responses depend on substrate spatial scale (Fig. 3).
Fig. 3 Spatial scale of substrate texture affects body patterning in cuttlefish. Animals showed a transition from uniform and mottle patterns to disruptive patterns as the substrate scale increases. However,
cuttlefish did not return to uniform patterns on the last few textures (S7–S9); rather they only showed weakened disruptive body patterning (modified from Chiao et al. 2009)
Background intensity It is typically assumed that variations in Weber contrast within a scene are more important in controlling behavior than the mean luminance of the scene; however, our results demonstrate that with other factors equal, substrates with lower mean luminance tend to evoke stronger disruptive responses (Fig. 4). This was revealed clearly by Chiao et al. (2007) who devised two substrates that comprised a regular array of light squares on a dark background in which
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Fig. 4 Background intensity regulates body patterning in cuttlefish. a–b Cuttlefish showed decreasing grades of disruptive body patterns on substrates composed of large light squares (100 %-WS-size) on dark backgrounds, in which mean intensity was steadily increasing and contrast was kept relatively constant. On the upper-left corner of each image panel, absolute intensity of each patch and the Weber contrast of the brightest patch are indicated. c Averaged disruptive scores of six cuttlefish on two substrates are significantly different
(p = 0.0364), and bars represent the standard errors. MI mean intensity; WC light-square Weber contrast. d–e Cuttlefish showed similarly decreasing grades of disruptive body patterns on substrates composed of medium light squares (12 %-WS-size) on dark backgrounds (with mean intensity and contrast varied as in a and b). f Averaged disruptive scores of six cuttlefish on two substrates are significantly different (p = 0.0129) (modified from Chiao et al. 2007)
the light squares subsumed 25 % of the area, and each light square was roughly equal in size to the white squares of the cuttlefish being tested. However, one substrate was darker than the other. In the darker substrate, the light squares had reflectance 0.43 and the background had reflectance 0.14, whereas in the lighter substrate, the light squares had reflectance 0.7 and the background had reflectance 0.21. Thus, the Weber contrasts of the squares in the darker and lighter substrates were 1.02 and 1.11, respectively. Despite the fact that its squares actually had slightly lower Weber contrast, the overall darker substrate evoked a significantly larger disruptive patterning response than the lighter substrate (Fig. 4c). A test using analogous substrates with squares scaled down in size by a factor of nine yielded an analogous result: the darker substrate evoked a significantly larger disruptive response than the lighter substrate (Fig. 4f). Thus, in cuttlefish, low background intensity tends to evoke stronger disruptive patterns.
However, other aspects of the animal’s pattern are likely to change as the contrast of a fixed-patterned background is manipulated. For example, when the contrasts of checkerboard backgrounds of different sizes were varied, on high-contrast checkerboards, cuttlefish body patterning depended on check size as described above, whereas on low-contrast checkerboards—irrespective of check size— cuttlefish showed low-contrast uniform/stipple patterns (Fig. 5) (Barbosa et al. 2008b; Zylinski et al. 2009a). As substrate contrast increased, so did the contrast of the animals’ body patterns, until at high contrast, full expression of either mottle or disruptive patterns was observed (Chiao et al. 2010). One might expect such changes in body patterning with increasing background contrast because visual predators are highly sensitive to differences in contrast. Effective camouflage for a benthic organism such as cuttlefish must deceive predators viewing from above as well as from the side; thus the choice of camouflage body pattern is expected to be sensitive to visible variations both in the ground plane (i.e., the horizontal substrate) and also perpendicular to the ground plane (i.e., vertical aspects of the visual background). Most experiments have dealt only with the former. When high-contrast background patterns
Background contrast Generally the response patterns produced by a cuttlefish tend to resemble the contrast of the benthic background.
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J Comp Physiol A Fig. 5 Contrast and check size influence body patterning in cuttlefish. For high-contrast levels, body patterning depends on check size, while for lowcontrast levels, body patterning is independent of check size. Disruptive coloration was shown on 40 % check area with highest contrasts. Uniform was elicited on all check areas for the lowest contrast levels. Mottle patterning was shown on the 10 and 3 % check areas for contrast values higher than 0.34 and 0.53, respectively (modified from Barbosa et al. 2008a)
were presented on the walls of the test arena, cuttlefish also emitted disruptive body patterns (Barbosa et al. 2008a). However, there were differences in the expression of disruptive pattern components if the checkerboard was presented simultaneously on the bottom and wall, or solely on the wall or the bottom. These results demonstrate that cuttlefish respond to visual background contrast variations both in the ground plane and also perpendicular to the ground plane (see 3D visual cues below). Since contrast of the background environment is crucial in determining cuttlefish body pattern, we applied this sensory rule to show that cuttlefish body patterns depend on the luminance contrast, not the chromatic contrast, of the substrates, supporting the finding that cuttlefish are color blind (Mäthger et al. 2006). This result is consistent with an earlier finding that cuttlefish change body patterns based on the contrast—not the color—of mixed gravels (Marshall and Messenger 1996). These studies emphasize
the importance of background contrast on cuttlefish body patterning. Object edges The edge of an object is an abrupt change in spatial properties between object and background, and it is known that the visual systems of many animals are highly sensitive to edges (Troscianko et al. 2009). However, complete edges of objects are rare in cluttered visual environments. Instead, edge segments (lines and corners) are more abundant in complex backgrounds. Thus, visual sensing of salient edges/lines in the background provides cuttlefish with rich information that can be potentially used to control disruptive body pattern expression. We and others have shown that cuttlefish body patterns are influenced strongly by visual edges in the substrate (Chiao et al. 2005; Zylinski et al. 2009b). In a recent study,
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Fig. 6 Continuous edges and line terminators influence expression of disruptive body pattern components via different mechanisms that are controlled by contrast in different ways. A gray field populated with randomly placed white disks was filtered into a high spatial frequency band to produce low-contrast full-edge rings (S3). Low-contrast, quarter-edge rings (S4) were produced by erasing a random 270 deg arc from each low-contrast full-edge-ring. High-contrast versions of these edge substrates were generated by maximizing the overall contrast (S5 and S6). High-contrast edge fragments evoked substantially stronger body pattern responses than low-contrast edge fragments, whereas the body pattern responses evoked by high-contrast continuous edges were no stronger than those produced by low-contrast edges (modified from Chiao et al. 2013)
J Comp Physiol A
choice of body patterns. An almost entirely homogeneous dark background that contains even a single white element of roughly the same area as the white square of the cuttlefish will evoke a disruptive body pattern (Chiao and Hanlon 2001a). This effect is specific to light objects; dark elements on the same background (with equal contrast to the background as the white elements) fail to evoke disruptive body patterns (Mäthger et al. 2007; Kelman et al. 2008). This response to sparse white background elements is surprisingly invariant with respect to their shapes (Chiao and Hanlon 2001b) or the size and age of the cuttlefish (Barbosa et al. 2007). In a recent study (Chiao et al. 2013), however, we found that although disks of both contrast polarities evoked relatively weak disruptive body patterns, black disks activated different skin components than white disks, and high-frequency information alone sufficed to drive the responses to white disks whereas high- and low-frequency information were both required to drive responses to black disks (Fig. 5 in Chiao et al. 2013). Thus, the patterning response is sensitive to the contrast polarity of the substrate; that is, the skin components activated by the substrate comprising black disks on a gray background tend to be dark, whereas those activated by white disks on a gray background tend to be light. This finding supports the concept that object contrast polarity plays a role in determining a cuttlefish’s body pattern type. Object depth and 3D
we systematically examined how cuttlefish body patterning is differentially controlled by various aspects of edges (Chiao et al. 2013). Strikingly, we found that high-contrast edge fragments (including abrupt points of termination) evoked substantially stronger body pattern responses than low-contrast edge fragments, whereas the body pattern responses evoked by high-contrast closed edges (i.e., circles without points of termination) were no stronger than those produced by low-contrast edges (Fig. 6). This suggests that line terminators vs. continuous edges influence expression of disruptive body pattern components via different mechanisms that are controlled by contrast in different ways. In addition, a recent study shows that cuttlefish respond to circles fragmented by gaps differently than they do to randomly scattered circle fragments (Zylinski et al. 2012). This suggests that cuttlefish are sensitive to the colinearity of the components in the circles fragmented by gaps.
Visual depth (both real and pictorial depth) appears to be one key in evoking disruptive patterns (Kelman et al. 2008). We also investigated the role of an isolated threedimensional object vs a continuous background substrate in controlling the patterning responses produced by cuttlefish (Buresch et al. 2011). We found that the three-dimensional object exerted a strong influence on patterning responses only if the object was marked by a high-contrast pattern (Fig. 7). In this case, cuttlefish showed a strong tendency to take their sensory cues from the pattern of the object. However, uniform gray objects exerted no measurable influence on responding. Thus, contrast of 3D objects is an important visual cue for masquerade (i.e., looking like another object rather than resembling the substrate; Stevens and Merilaita 2011). This study also supports the important role of object contrast as a cue in the cuttlefish’s preference to resemble 3D objects rather than the benthic substrate. Regulation of 3D physical skin texture and arm posture
Object contrast polarity The presence of white (or light) elements on the dark background is an important factor regulating a cuttlefish’s
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Cephalopods are unique in the animal kingdom for having neurally controlled muscular papillae in the skin to quickly change the shape of their skin from smooth to
J Comp Physiol A
Fig. 7 Presence of 3D objects modulates body patterning in cuttlefish. Animals were tested for a preference to show a body pattern appropriate for the 3D object or the benthic substrate. Cuttlefish
responded by masquerading as the 3D object, rather than resembling the benthic substrate, only when presented with a high-contrast object on a substrate of lower contrast (modified from Buresch et al. 2011)
highly rugose; i.e., from flat 2D to papillate 3D. Allen et al. (2009) conducted experiments to determine whether S. officinalis use tactile or visual cues to control papillae expression (because hypothetically they could acquire tactile information from the suckers on their arms). Cuttlefish were placed on natural substrates to evoke the three major camouflage body patterns: Uniform, Mottle and Disruptive. Three versions of each substrate were presented: the actual substrate, the actual substrate covered with glass (removes tactile information) and a laminated photograph of the substrate (removes tactile and three-dimensional information because depth-of-field information is unavailable). No differences in papillae expression were observed among the three versions of each substrate; thus visual (not tactile) cues drive the expression of papillae. However, there were no tests to determine which visual background cues were eliciting papillae expression. Similarly, cuttlefish deploy some of their arms (they have 8) upwards and sideways when they are camouflaging themselves adjacent to vertical objects that have relatively thin protrusions (e.g., branches of a soft coral or alga) to enhance their camouflage via body posture. Barbosa et al. (2012) demonstrated experimentally that S. officinalis adjust the orientation of their raised arms to align with the orientation of stripes on a wall (horizontal, 45°, and 90°); when there were no stripes, the cuttlefish did not raise their arms at all (Fig. 8). In these experiments, the visual stimuli were high-contrast (black and white) stripes, each the width of the animals’ arms. Field photographs and video confirm these results from the laboratory. Collectively, these studies show that the eyes are sensing the vertical orientation of adjacent objects to guide arm postures, and are also able to sense the fine 3D texture of adjacent backgrounds and generally replicate that in their skin.
Scene analysis and feature integration for rapid camouflage body patterning How does a cuttlefish so quickly analyze the scene and put on an appropriate body pattern to conceal itself within a given background? Part of the answer lies, we believe, in the counterintuitive finding that cuttlefish appear to have evolved only 3 basic pattern templates (Uniform, Mottle, Disruptive, each with variation) with which to achieve concealment (e.g., Hanlon 2007). Thus, one working hypothesis is that the pattern deployed by a cuttlefish in response to a particular visual background reflects a two-stage process in which a relatively simple set of “visual sampling rules” is first used to select one of the three basic pattern types, which is then further refined in a second stage of processing that depends on subtler statistical features of the background. A somewhat comparable idea has been proposed by Zylinski et al. (2009a), in which a simple model focusing on cuttlefish edge detection is used to determine pattern types, then finer control of skin coloration is modulated by other substrate features. In any case, it is the remarkable speed of change (including orchestration of 2–3 million chromatophore organs in the skin) that suggests some sort of refined parsimonious visual sensing/perception process. It is apparent that multiple visual features including spatial scale, background intensity, background contrast, object edges, object contrast polarity, object depth, presence of 3D objects, etc., are important cues for cuttlefish to achieve effective camouflage (Hanlon 2007; Hanlon et al. 2011; Zylinski and Osorio 2011; Zylinski et al. 2009b). We can think of the eye as a sensor of diverse visual backgrounds, and cuttlefish acquire visual information by actively sensing surrounding environments with vertebratelike eyes (Packard 1972; Messenger 1991). The detailed
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J Comp Physiol A
Fig. 8 Cuttlefish adjust their arm postures visually according to the orientation of stripes on the wall of the aquarium, thus enhancing camouflage via posture. Field images show cuttlefish raising arm pos-
tures similarly when settled next to vertically oriented algae and corals (modified from Barbosa et al. 2012)
structure and functions of the cuttlefish eye are rather peculiar, however: a W-shaped pupil, polarization sensitivity, no color vision, good visual acuity, and good night vision. Significant visual processing that extracts multiple visual features of substrates occurs in the optic lobe, the largest brain area in cephalopods. The parallel nature of this visual information processing is somewhat akin to human vision (Zylinski and Osorio 2011). However, little is known about feature integration in the cuttlefish brain and the resultant motor act that produces the body pattern for camouflage. Earlier studies have shown that stimulating the optic lobe alone with extracellular electrodes generates whole body pattern changes (Boycott 1961; Chichery and Chanelet 1976). Thus, it is likely that the optic lobe is the neural substrate in which cuttlefish integrate these visual features and determine the appropriate body pattern types for camouflage. After the stage of pattern selection (action planning), various skin components—which are controlled by physiological units in the brain innervating motor fields on the skin (Packard 1982)—are activated selectively to generate body patterns. This processing stage is probably under the neural control of the lateral basal lobes (intermediary motor centers) and chromatophore lobes (lower motor centers) (Messenger 2001). Motor neurons in the chromatophore lobes extend directly (without synapse) to chromatophore organs throughout the skin. Thus, the coordinated neural signals from a hierarchy in the brain excite radial muscles controlling the expansion of chromatophore organs in the
skin and generate appropriate body patterns for camouflage. Additionally, neural signals excite muscular hydrostats that erect skin papillae as well as arm muscles to position the arms for postural camouflage. The entire process (minus papillae and arm postures) is summarized in Fig. 9, which illustrates our current representation of visual perception and motor control mechanisms that regulate rapid adaptive camouflage in the cuttlefish S. officinalis. There are several marine fishes capable of rapid adaptive camouflage but practically no research on the visual perception that guides pattern choice. With winter and summer flounder, Saidel (1988) concluded that both mean reflectance and contrast of the background have an influence on body pattern. Ramachandran et al. (1996) found that the tropical flounder Bothus ocellatus had three basic camouflage patterns that responded to checkerboards, sand, and gravel but performed no experiments to probe visual perception of the fish. Kelman et al. (2006) found two basic body patterns under active control in plaice (Pleuronectes platessa) but did not address the visual perception of the fish. Tyrie et al. (2015), in a field study of the coral reef flounder Bothus lunatus, found two pattern types (uniform and mottle) that the fishes chose to deploy after selecting certain substrates and avoiding others. Here, the eyes were not only using surrounding benthic visual information to decide on uniform or mottle patterns, but were using visual input to select certain substrates over others.
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J Comp Physiol A
Fig. 9 A schematic representation of neural processing stages in cuttlefish camouflage behavior. Cuttlefish acquire visual information by actively sensing surrounding environments with vertebrate-like eyes (visual input). Significant information processing then takes place in the optic lobe to extract multiple visual features of substrates (visual processing). Essential visual cues known to affect cuttlefish camouflage include spatial scale, background intensity, background contrast, object edges, object contrast polarity, and object depth, etc. Cuttlefish then integrate all of these visual features and determine the appro-
priate body pattern types for camouflage, presumably in the optic lobe (pattern selection). To generate the selected body pattern, various skin components responsible for the composition of these body pattern types are selectively activated, perhaps under neural control in the lateral basal lobes and the chromatophore lobes (pattern generation). Finally, the coordinated neural signals from the brain excite radial muscles controlling the expansion of chromatophore organs on the skin and generate appropriate body coloration and patterning for camouflage (motor output)
Conclusion and future research
known in some detail (the subject of this review), but the mechanisms that control the fine tuning of each of these pattern types have barely been studied. Continued detailed psychophysical studies such as those by Zylinski et al. (2009a, 2012) and Chiao et al. (2013) are warranted in this respect. In addition, assessing body patterning on more natural and complex backgrounds (similar to Allen et al. 2010; Mäthger et al. 2007) is likely to shed light in understanding the interplays of these basic features in eliciting body pattern types. Another potentially fruitful approach seeks to analyze the dynamics of cuttlefish patterning responses by presenting stimulus substrate patterns whose properties are varied in real time, in ways that depend on the response patterns they elicit. This approach will most likely require special display technology that reflects ambient light rather than creates light; cuttlefish react poorly to displays that emit light. Moreover, Liquid Crystal Display monitors are not suitable because cuttlefish are highly sensitive to the variations in light polarization that are used to produce different intensities in such displays. However, display
Cephalopods combine keen visual sensing of backgrounds with neurally controlled skin patterning to achieve rapid adaptive camouflage patterns that are linked inextricably to camouflage behavior. It takes large segments of a complex nervous system to coordinate these patterns, which may partly explain why most other animals have not evolved such diverse adaptive camouflage. In this respect, it would be rewarding to study the visual perception mechanisms of the few marine teleost fishes that change camouflage rapidly. The effectiveness of the patterning strategies used by cuttlefish in eluding detection suggests that analysis of these strategies can provide key insights into the visual processes of predators (e.g., texture segregation, edge extraction, and object recognition). Many avenues of future research promise to deepen our understanding of this visual sensorimotor system. In general, the basic features that stimulate deployment of the main pattern types (Uniform, Mottle, Disruptive) are
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technologies that solely reflect light without a polarization signature (such as cholesteric displays) offer a promising option. Many open questions remain concerning cuttlefish physiology. For example, how do cephalopods accomplish color-blind camouflage? Cuttlefish color resemblance to backgrounds in nature appears to be very good (e.g., Hanlon et al. 2013) yet they are color blind (Marshall and Messenger 1996; Mäthger et al. 2006). Opsin molecules in the skin may provide some form of light sensing that affects body patterns (Mäthger et al. 2010) although they may not be for color matching. As for processing of visual information, practically nothing is yet known about the level of this in the retina of S. officinalis, except some recent studies on cephalopod eyes that revealed their contrast sensitivity and spatial resolution (Mäthger et al. 2013; Nilsson et al. 2013; Chung and Marshall 2014). Although there is basic information on the gross anatomy of the optic lobes of Octopus and the squid Loligo (Young 1962, 1974), the fine connections and the physiology remain unstudied. The functional roles of the other brain centers involved in body patterning expression (particularly the lateral basal and chromatophore lobes) remain mostly unstudied in Sepia although there are various studies of these lobes in other cephalopods (summarized in Messenger 2001). The processes controlling peripheral innervation and activation of the pigmented chromatophore organs and the structural coloration cells (iridophores) are poorly understood (Messenger 2001; Gonzalez-Bellido et al. 2014; Tublitz et al. 2006). Challenges to the hypothesized scenario projected in Fig. 9 are welcomed, particularly papers that are experimental in design.
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