A basic understanding of dog vision has been available for over two decades, with an extensive review being published by P. E. Miller and Murphy (1995). Advances in canine vision science since then have been limited, and this remains an excellent in-depth overview of many aspects of the dogs’ visual system. However, in the last two decades, the amount of research conducted with dogs, and the way their cognitive skills are assessed, has drastically changed. For example, experiments now involve visual stimulus presentation (e.g., Pongrácz, Miklósi, Dóka, & Csányi, 2003), and touch-screens (e.g., Range, Aust, Steurer, & Huber, 2008), to name a few. Therefore, we begin this review with a brief overview of vision in dogs, specifically highlighting aspects of dog vision that may affect perception during modern visual cognition tasks.

Fundamentals of dog vision

While dogs appear to be visual generalists, with functional vision during both the day and night (Duke-Elder, 1958; Walls, 1942), they appear to be more scotopic than humans, meaning that they are highly adapted to function in dim light. In fact, they appear to have developed several ways of improving visual functioning across a variety of ambient light levels. The retina of the dog is largely composed of rod photoreceptor cells, which are extremely helpful in dim light as they can function in less intense light conditions (Kemp & Jacobson, 1992). Only 3 % of retinal cells in dogs are cone photoreceptor cells, which are primarily responsible for color vision (Peichl, 1992). This compares with roughly 5 % in humans (Purves, Augustine, & Fitzpatrick, 2001).

Although a foundational understanding of rod and cone photoreceptor cells in dogs is available, only recently have scientists furthered our knowledge of their precise distribution. Mowat et al. (2008) observed that the area centralis, a region typically centrally located in the retina, contains the maximal density of rod and cone photoreceptor cells in dogs. Even though cone photoreceptor cells are more numerous in the central portion of the retina (20 % of all receptors) (Koch & Rubin, 1972; Parry, 1953; Peichl, 1992), the area centralis in dogs does not consist exclusively of cones as it does in humans (Mowat et al., 2008). These newer findings are consistent with older work, some of which is reviewed below, suggesting that dogs may be more adapted to dim light conditions and less sensitive to color perception than humans. If so, this would have clear implications for cognitive tests requiring color discrimination.

Sensitivity to light

While both dogs and humans utilize rod photoreceptor cells to function in dim light conditions, the rod photo pigment, rhodopsin, differs between the two species. Rhodopsin, a g-protein-coupled receptor, is highly sensitive to light and improves vision in dim light conditions. Dogs typically have a rhodopsin peak sensitivity to light wavelengths of 506–510nm (Jacobs, Deegan, Crognale, & Fenwick, 1993; Kemp & Jacobson, 1992; Parkes, Aguirre, Rockey, & Liebman, 1982), while humans have a peak sensitivity to slightly shorter wavelengths of 495 nm (Kraft, Schneeweis, & Schnapf, 1993). As the peak rhodopsin wavelength sensitivity hardly differs between dogs and humans, it appears that the dog’s enhanced vision in dim light conditions may be due to other attributes (P. E. Miller & Murphy, 1995). However, additional research is required to substantiate such claims.

One attribute that increases dogs’ sensitivity in dim light conditions is the reflective tapetum lucidum. This superiorly located layer of tissue in the eye is a biologic reflector system commonly found in vertebrates (Ollivier et al., 2004), but not in humans. Typically, the tapetum lucidum offers light-sensitive retinal cells an additional opportunity for photon-photoreceptor stimulation by reflecting light, which has already passed through the retina, back through it a second time. This reflection enhances visual sensitivity in dim light conditions, but typically reduces the ability of the eye to observe details of an image due to increased scattering of light in the eye (Walls, 1942).

Perhaps surprisingly, there is variation in dogs’ tapetum lucidum (Granar, Nilsson, & Hamberg-Nyström, 2011; Lesiuk & Braekevelt, 1983). A strain of laboratory beagles has been observed to have hereditary tapetal degeneration (Burns, Bellhorn, Impellizzeri, Aguirre, & Laties, 1988) and, in a sample of 539 dogs, a tapetal area was completely present in only 70.3 % of them, being completely absent in 1.9 % (Granar et al., 2011). Generally, smaller sized breeds, like Papillons, Shetland Sheepdogs, Dachshunds, American Cocker Spaniels, Miniature Schnauzers, Miniature Poodles, Bichon Frisé/Havanais, and Cavalier King Charles Spaniels, have a smaller tapetal area, while larger dogs, like Border Collies, Leonbergers, Samoyeds, Golden Retrievers, and English Springer Spaniels, typically have a full-sized tapetal area (Granar et al., 2011). Labrador Retrievers have smaller than expected average tapetal size because there appears to be increased variation within the breed. Specifically, a large proportion of Labradors lack a tapetal area. Thus, it appears that the size of the tapetal area depends largely on breed and body size, but that marked variation may also exist within a breed.

Since the main function of the tapetum lucidum is to facilitate detection of small amounts of light, perhaps dogs without a tapetum lucidum are worse at discriminating between light conditions. We were unable to uncover evidence for such an effect, and the previous review on vision in dogs claimed that no functional differences had been reported (P. E. Miller & Murphy, 1995). Regardless, as this kind of variability within a species is uncommon, it should be investigated further using modern, technologically advanced equipment and techniques. We recommend future research attempt to evaluate the effects of tapetal-area differences, or develop a method for easily observing such differences so that researchers can be aware of potential physiological differences within their sample.

Finally, as dogs are sensitive to a variety of light conditions, this can affect their recovery from exposure to bright light. The phenomenon of photo bleaching occurs when photo pigment becomes almost transparent following exposure to light, after which it must regenerate to regain pigmentation when in the dark. The regeneration from rhodopsin’s photo bleaching effects is longer in dogs (over an hour) than in humans (approximately 30 min). This means that when a dog and a human come inside after having been outside, the recovery time from the photo bleaching effect is twice as long in dogs as it is in humans. Because abrupt changes in light conditions could more drastically affect dogs than humans, this should be considered when bringing dogs from bright outdoor environments directly into indoor laboratories for cognitive testing.

Brightness discrimination

As dogs appear to have evolved as visual generalists, it may be assumed that their sensitivity to differences in brightness would be quite good. However, two relevant studies provide conflicting reports. Stone (1921) observed relatively low brightness discrimination thresholds for two fox terriers, comparable with thresholds observed in humans. By calculating the smallest difference between two stimuli that the dogs could detect, Stone (1921) determined Weber fractions of 0.12 and 0.10, a result quite comparable to the 0.11 observed in humans (Griebel & Schmid, 1992). However, he only assessed the dogs on one standard brightness intensity, a potential limitation as psychophysical studies on humans demonstrate that brightness discrimination thresholds decrease with increasing light intensity (Craik, 1938)

More recently, Pretterer, Bubna-Littitz, Windischbauer, Gabler, and Griebel (2004) observed that brightness discrimination was about two times worse in dogs than it is in humans, with reported Weber fractions of 0.22 and 0.27 for three subjects, a German Shepherd and two Belgian Shepherds. This result suggests a relatively high brightness discrimination threshold for dogs compared to Stone (1921). It has been previously suggested (Scholtyssek, Kelber, & Dehnhardt, 2008) that the high threshold observed by Pretterer et al. (2004) is likely a result of the experimental methods and may underestimate the brightness discrimination capabilities of dogs. In the experiment, dogs were required to discriminate between stimuli of various intensities that were 1.1 m apart, a reasonably large distance that may have affected the subject’s choices and, consequently, the threshold observed. Additional research is required to evaluate the findings of these two studies.

Visual acuity and spatial resolution

Visual acuity refers to the clarity of vision and is dependent on optical and neural mechanisms (e.g., eye structure, the health of the eye, the brain’s interpretation). While dogs’ visual acuity is difficult to measure, it is typically estimated to be considerably worse than humans’. Based on a variety of studies employing different methods, such as behavioral testing, measurement of visually evoked cortical potentials, pattern electroretinography, and optokinetic responses, P. E. Miller and Murphy (1995) estimated the visual acuity of a typical dog to be 20/75. This value suggests that, from 20 feet away, a dog could perceive an object that a person with normal vision could differentiate from 75 feet away.

A lack of visual acuity in dogs is not surprising, as there is likely a trade-off that exists in dog vision. Considering the physiology of the dog eye discussed above, and the dim light conditions to which it is adapted, dogs may be more sensitive to light at the expense of being able to discriminate smaller details. Whether the exact value of 20/75 reported by P. E. Miller and Murphy (1995) is correct or not, however, has proved difficult to determine.

Murphy, Mutti, Zadnik, and Ver Hoeve (1997) assessed visual acuity in three young adult Beagles using sweep visual-evoked potentials. This method allows for visual acuity estimates by measuring the cortical response to a sequence of gratings of increasing spatial frequency. Visual acuity estimates were between 20/45 and 20/85. More recently, a behavioral assessment of visual acuity has been conducted by Tanaka, Ikeuchi, Mitani, Eguchi, and Uetake (2000). These authors reported visual acuity estimates of 20/60 to 20/85 in three Shiba dogs.

Even taking into account the fact that differences in acuity estimates are also highly variable in other species, with those obtained through behavioral investigations often indicating lower acuity than electrophysiological acuity measures (Murphy et al., 1997), these disparate estimates suggest that further work is required. It would be of great interest to know whether all dogs have similar levels of visual acuity or vary systematically according to breed, morphology, or other factors. Such research would allow cognition researchers to more accurately create appropriately sized stimuli and viewing distances, such that dogs would be capable of perceiving them.

Depth perception

Binocular overlap refers to the overlapping portion of a visual scene that is viewed by both eyes. Due to our forward facing eyes, and relatively unobtrusive noses, humans have a degree of binocular overlap of roughly 140° (Walls, 1942). In dogs, various estimates of binocular overlap exist and these vary based on the immense variation in facial morphology types as well as the methodology used to calculate the estimates. P. E. Miller and Murphy (1995) report that, in behavioral studies, binocular overlap has been estimated to be roughly 30–60°. However, it can be anywhere from 35° to 40° when calculated based on ganglion cell density (Peichl, 1992), and 80–116° when calculated based on optical considerations (Duke-Elder, 1958; Walls, 1942).

Depth perception, or stereopsis, represents the visual ability to perceive the world in three dimensions (3-D) and is enhanced in regions where both eyes have overlapping fields of view. This occurs when both eyes view the external world from different vantage points and the information is merged to create a single image. It is this fusion of image that allows the eye to accurately perceive depth (Bishop, 1987). In a visual cliff experiment, young puppies demonstrated outstanding monocular (single eye) and binocular depth perception (Walk & Gibson, 1961). Considering the canine eye does not completely develop until they are juveniles or young adults (a few months of age), P. E. Miller and Murphy (1995) suggested that adult dogs likely have even better visual depth perception. Additional research is needed to substantiate these claims, however, as studies of retinal ganglion cell topography suggest that depth perception in dogs may be impaired. Dogs lack alpha, also termed “Y,” ganglion cells, in both the right and left portions of the 15° of the peripheral binocular overlap (Peichl, 1992). Thus, it is possible that there is a smaller area of binocular overlap where the retina perceives high quality depth perception. Additional research is clearly required to confirm available information, and also to determine if depth perception varies systematically by breed.

Color vision

The dog’s ability to distinguish different colors remains controversial. Humans have three types of cone photoreceptor cells (long-wave (red), medium-wave (green), and short-wave (blue), at spectral peaks of 558 nm, 531 nm, and 419 nm, respectively). Dogs have only two, which almost identically correspond to short-wave and long-wave sensitivities (blue at a spectral peak of 555 nm and yellow at 429 nm) (Jacobs et al., 1993; Neitz, Geist, & Jacobs, 1989). This has been used to suggest that dogs may be unable to perceive differences between green, yellow, and red color cues. Accordingly, early studies suggested dogs lacked good color vision (Neitz et al., 1989). However, there is some even older evidence that suggests dogs may be able to perceive these colors (e.g., red and green) even without possessing the cone photoreceptor cells believed to be responsible for this ability (Rosengren, 1969). More research is needed to understand the extent to which dogs perceive color, and how similar dog color perception is to that of non-color-blind humans.

Even with this limitation in mind, dogs appear to be attentive to the colors they can perceive. Two Shiba dogs were able to appropriately identify a positive stimulus (red, blue, or green compared to grey) in a two-choice discrimination task, where the light intensity on the cards was 450–500 lux (Tanaka, Watanabe, Eguchi, & Yoshimoto, 2000). The authors of this study suggested that color vision is relatively well developed, considering the dogs were able to discriminate between all three primary colors and grey. Another study showed that, under natural photopic lighting conditions, dogs might preferentially use color over brightness cues, when presented with yellow and blue stimuli in a discrimination task (Kasparson, Badridze, & Maximov, 2013). Eight dogs were observed to use color over brightness cues when discriminating and recognizing visual objects (Kasparson et al., 2013). These findings suggest that color may be a fundamental feature of visual objects as perceived by dogs. However, additional research is needed to assess their performance in various light conditions.

In addition to their preference for color cues, it appears that dogs may have a capacity to perceive ultraviolet light (Douglas & Jeffery, 2014). In a cross-species assessment of ultraviolet (UV) sensitivity in mammalian eyes, dogs were identified to have lenses transmitting significant amounts of UV rays (335 nm). This suggests that even though dogs do not have a specific UV visual pigment, they may be sensitive to ultraviolet light (Douglas & Jeffery, 2014). If this is the case, cognition researchers must begin to determine the UV light levels that dogs can perceive, and consider the effects this may have on the stimuli and conditions in which they are being assessed.

Finally, there is evidence to suggest that dogs may have a magnetic sense associated with their visual system. A recent study observed the presence of cryptochrome 1, a flavoprotein located in the canine eye that is sensitive to blue light. Additionally, it is involved in responding to light-dependent magnetic orientation based on the earth’s magnetic field (Nießner et al., 2016). These authors suggest that this does not likely act as an additional pigment for the perception of color, but instead likely functions to perceive the earth’s magnetic field.

Sensitivity to monitors

Sensitivity to flickering lights has become relevant in the study of dog cognition due to the frequent use of screen-presented stimuli in cognition tests. The flicker fusion rate is the point at which rapidly flickering light appears to meld into a constantly illuminated light. This is important when presenting videos as these rely on presenting a rapid succession of static images. If the frame rate, in Hertz (Hz), is below the threshold of sensitivity, the flicker will be viewable and the film will appear jerky. Therefore, studying flicker fusion rates offers insight into the functional qualities of dog visuoperception.

Originally, electroretinographic studies of anesthetized dogs suggested they could detect flickering up to a maximum of approximately 20 Hz (Gustavo Aguirre, 1978; GD Aguirre & Rubin, 1975). However, behavioral paradigms using unanesthetized dogs suggest a more sensitive flicker detection, approximately 70–80 Hz. More recently, Healy, McNally, Ruxton, Cooper, and Jackson (2013) observed flicker fusion frequencies to be 80 Hz in dogs compared to 60 Hz in humans. This is potentially a major problem for dog cognition studies, as these findings suggest that dogs are more sensitive to flicker than humans, and more sensitive than could easily be accommodated by some screens currently in use. What appears as a fluidly moving video image to humans may appear as a flickering image to dogs, making it difficult to determine if their performance on relevant tests is a genuine indicator of their cognitive abilities.

Furthermore, it is possible that the presentation of static images on a monitor is also affected by dogs’ greater sensitivity to flicker-fusion rates. Refresh rates, the number of times in a second that a display renews an on-screen image, may also be perceived differently by dogs than by humans. For example, cathode ray tube (CRT) monitors are typically set to present at 60–70 Hz for humans, in order to avoid viewing of flickering. While CRT monitors are no longer common, they may be used in some research contexts depending on the aims of the study. For example, CRT monitors tend to maintain a more stable brightness than modern liquid-crystal display (LCD) monitors. LCD monitors typically exhibit no refresh rate-induced flicker, and are commonly set to present at 60 Hz (although given technological advancements there is increased variation in this value). Unlike CRT monitors, pixels on LCD monitors do not necessarily flash on/off between frames. Therefore, the flicker effect often observed on older screens may no longer be a potential confound as long as the flicker-fusion rate is above the threshold observed in dogs. Considering these physiological differences (compared to humans) it is important to utilize proper technological tools, as well as to be aware of how differences in physiology may indirectly affect experimental outcomes.

Part 1 conclusions

In summary, while the visual system of dogs may be considered to be worse than that of humans in many ways (P. E. Miller & Murphy, 1995), it is evident from our review that, in some ways, their vision is superior, or at least different. It seems that the visual acuity and color perception capabilities of domestic dogs are less sensitive than those observed in humans, but the observed flicker-fusion rate, and their ability to function in dim light, surpass those of human capacities. Of most relevance here is that many aspects of dog vision remain substantially understudied. Moreover, many studies have used extremely small sample sizes, often comprising a single breed, and, as a result, individual, breed, and morphological differences have rarely been considered (for a review see Arden, Bensky, & Adams, 2016).