Synonyms

Related: Visual senses

Definition and Psychological Perspectives on Visual Perception

Visual perception is a brain process that actively detects and interprets neurological signals that were transduced from light. Much of what is known about visual perception has been well studied and understood with respect to human vision. The understanding of visual perception varies among researchers within behaviorism, Gestalt psychology, and cognitive psychology (Gregory 1997).

Behaviorists focus less on the inner workings of the mind and demonstrate that learned behavior is explained by chains of conditional responses. This behavioral explanation for visual processing falters, as perception is said to be a function of stimuli directly, rather than as a result of the internal processing of the mind related to those stimuli (Gregory 1997).

In Gestalt psychology, visual perception is interpreted as being greater than the sum of stimuli that make it up and organizing heuristics are based on certain laws, such as closure, common fate, and contiguity of close-together features (Gregory 1997). The law of closure describes a pattern when an image is incomplete but is arranged in such a way where an observer is able to describe a complete image, even with missing information (i.e., the Kanizsa’s Triangle, Fig. 1) (Gregory 1997). Common fate occurs when objects are moving in the same direction, and as a result, they appear as moving “together.” Contiguity of close-together features describes how the brain organizes shapes when objects are positioned close together, so they appear as a group to an observer.

Fig. 1
figure 1

Kanizsa’s Triangle: These spatially distinct fragments imply a bright white triangle, defined by a sharp illusory contour covering three black circles and a black-outlined triangle

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Cognitive processes related to problem solving and visual perception have historically been thought of as separate from one another. Early physiological psychologist Hermann von Helmholtz viewed perception as unconscious inferences, therefore pivotally linking thought to visual processing. Cognitivists focus less on the relationship between stimulus controls of perception and behavior but emphasize general knowledge, learning, memory, attention, and logical thinking as focal points in the study of visual perception with varying degrees of success (Gregory 1997).

Visual Biology, Perception, and Cognition

Visual perception is informed both by neurobiology and cognitive science (Clemente et al. 2010; Domjan and Grau 2015; Shimojo et al. 2001). The visual process occurs when light hits the retina, stimulating a change in opsin protein configuration in photoreceptors and flooding a transducing cell with sodium ions. Photoreceptors are not spread evenly on the retina, as the greatest concentration of rods can be found in the peripheral areas, while high-resolution cones are concentrated in the central fovea (Breedlove and Watson 2017). Light stimulation in photoreceptors causes a graded potential in bipolar cells that are, interestingly, positioned in front of the retina where light goes to stimulate transduction. This arrangement has interesting implications for visual perception in the brain as a great deal of “post-processing” is necessary for a clear image to form in the mind. Further positioned in front of the retina are the ganglion cells which together form the optic nerve where information is sent to the brain (Shimojo et al. 2001). The process from sensation to perception in the brain is a multichanneled path (Fig. 2) organized by early, form, and movement processing.

Fig. 2
figure 2

Visual processing pathway. LGN lateral geniculate nucleus, V1 primary visual cortex, V2 V3, and V4 visual areas 2, 3, 4, 5 and IT inferior temporal cortex. Area V1 is associated with spatial frequency recognition, orientation, and color perception. Area V2 is involved with form identification, specifically illusory contours of images. Area V4 has a role in form identification. IT functions in recognizing complex images, such as facial recognition. Area V3 is involved in global movement perception, while area V5 (MT = middle temporal) functions in motion detection and control of eye movements

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Early processing: Frequencies and contours. The visual cortex of the brain is divided into areas that have specialized contributions to the visual system (Breedlove and Watson 2017). The primary visual cortex in mammals (area V1) contributes to the recognition of spatial frequencies (Fig. 3), orientation, and color (Hubel and Wiesel 1962). V2 processes additively to what V1 does and adds information by aiding in the perception of contours (von der Heydt et al. 1984). Mainly fed by neurons from the Lateral Geniculate Nucleus (LGN), area V1 has within it a series of neurons organized into ocular dominance columns (ODCs) that benefit spatial frequency recognition (Shmuel et al. 2010) and are thought to be important in binocular vision (c.f. Horton and Adams 2005). The ODCs consists of cell bands that respond to various stimuli presented to an individual (Breedlove and Watson 2017). This was first identified by Hubel and Wiesel in cats through their responses to the orientation of light stimuli at the neuronal level. Slits of light as well as rows of dots with the same orientation were used to stimulate cells in the retina. From there, the signal was traced to cell units in the V1 area of the visual cortex. The experimenters isolated each eye to record the relative contribution of the monocular signals, before looking at the contributions of both eyes in aggregate. This experiment paved the way for understanding how visual physiology ultimately shapes perception and therefore represents a foundational work of neurobiology (Wurtz 2009). From a proximate viewpoint, Hubel and Wiesel also laid out the columnar organization of neurons in V1, showing convergence with the somatosensory cortex in mammals (Mountcastle 1957).

Fig. 3
figure 3

Spatial frequencies. High and low frequencies and contrasts that area V1 aids in recognizing. (a, b) The spacing between dark and light stripes shows that part a has double the spatial frequency of part b. (c, d) Visual grids with sinusoidal modulation of intensity: (c) high contrast; (d) low contrast. (e–g) A photograph of a young woman subjected to spatial filtering: (e) normal photograph; (f) high spatial frequencies filtered out; (g) low spatial frequencies filtered out. (Parts e–g courtesy of Jason Bruck). Figure adapted from (Rosenzweig et al. 1998) with permission from authors and publisher

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“What” processing: Shapes and forms. Area V4’s role is more firmly related to form and attentional processing and has neurons tuned to simple shapes as it takes input from V1 and V2 (Moran and Desimone 1985). Areas V2, V4, and the IT are involved in form identification, but each area has a specific role. For example, area V2 specializes in the interpretation of images with contours that project an illusion. Although, it is thought that V1 might feedback into this process (Ramsden et al. 2001), it is really V2 leading to higher cortical areas that is responsible for our perception of things like the brightness of negative space in the Kanizsa’s Triangle illusion (Fig. 1). V2 is tuned to aspects of spatial frequency and color and is thought to relate to object recognition memory (López-Aranda et al. 2009).

Both V1 and V2 mostly rest on the geniculate system; however area V4 is part of the extrageniculate or pulvinar system (although it has strong connections to V1 and V2) (Roe et al. 2012). This is a parallel pathway outside direct mediation by the LGN (Tabei et al. 2015). Just like V2, this structure has cells that respond to spatial frequency and orientation, but there are also cells with a stronger preference to respond toward different wavelengths of light. Much focus of late has been on the role of V4 in top-down visual attention processing and bottom-up object recognition (Roe et al. 2012). The IT contributes to recognizing complex forms (Breedlove and Watson 2017) and is the final area for visual object processing. The IT also contains specialized processors for recognizing specific kinds of objects, such as faces (Tsao et al. 2006). Individual experiences may shape how the IT area processes these stimuli, indicating connections with other cortical areas (Breedlove and Watson 2017).

Where things are: Location processing. Areas V3 and V5 aid with perception of motion (Born and Bradley 2005). V3 is thought to function in our processing of global movement and V5 functions in motion detection and control of eye movements (Dursteler et al. 1987). While the exact organization of V3 is up for some debate, V5 is also part of the extrageniculate system, but this center is not functionally additive the way V1, V2, and V4 are and has separate pathways for foveal vs. peripheral signals (Palmer and Rosa 2006).

Color Perception

Neurology of Color Perception

The assignment of color occurs in three stages (Breedlove and Watson 2017; Shimojo et al. 2001). The first stage (transduction) occurs on the cone photoreceptor itself. The second stage of processing occurs within the secondary neuronal tissue of the retina where inhibition and excitation of surrounding circuits play a role in shaping the signal that is inevitably sent to the brain (Kuffler 1953). From there the signal is sent through the LGN to area V1 where information is sent to other areas of the visual cortex to which color perception is finalized in the third stage (Breedlove and Watson 2017).

Theories of Color Perception

Within the science of color vision, there are opposing hypotheses of which neither is fully capable of explaining color vision: trichromatic theory (Young 1802) and opponent-process theory. The trichromatic hypothesis supports the idea that there are three different cone receptors, blue, green, and red, each with their own path to the brain (Young 1802). This is exhibited in certain primate species, while other mammalian species have dichromatic vision (Breedlove and Watson 2017). In contrast, the opponent-process theory (which applies to more processes than just color vision) supports the idea that there is a production of opposite reactions in response to different wavelengths of light (Breedlove and Watson 2017). Ewald Hering postulated about three independent receptor types which all have opposing pairs: white and black, blue and orange, and red and green. This would later be refined to two pairs, blue and yellow and red and green, where excitatory and inhibitory patterns of firing would affect the ultimate perception of color with the two components of each mechanism ultimately opposing each other. Therefore, one can have colors that appear greenish-blue or blueish-red, but not reddish-green or yellowish-blue. Neither hypothesis can explain color vision by itself; however the trichromatic theory explains how the three types of cones detect different wavelengths, while opponent-process theory explains how the cones connect to the ganglion cells, where the opposing elements inhibit each other to determine how color is perceived (Hurvich 1985).

Individual Differences

Color perception varies between organisms since there are differences in wavelength sensitivity as well as the availability and distribution of an organism’s rods and cones (Shettleworth 2010). In humans, different photoreceptors are sensitive to different wavelengths of light, with cones having peak sensitivity to 420 nm, 530 nm, and 562 nm and rods having peak sensitivity to 500 nm (Fox 2016). Humans can observe shadows as both dark and blue, whereas nonhuman animals with UV vision can see shadows as dark with shades in the UV spectrum (Troscianko et al. 2009). Many features of the eye, such as the sclera or corneal epithelium, are developed to suit an organism’s habitat and the types of color stimuli they experience on a daily basis (Berta et al. 2015). For example, the increase in water depth results in loss of color sensitivity which is shown in the retina of the red-tailed black shark whose eye consists mainly of rods and green and red-sensitive cones (Levine and MacNichol 1982). For most mammalian species with color vision, G. H. Jacobs proposed a range of color vision into four categories (Breedlove and Watson 2017). Diurnal primates, like humans, exhibit exceptional trichromatic vision. Dogs and pigs have two types of cone photopigments and large number of cones which results in a strong dichromatic vision. A weak dichromatic vision is present in species such as cats and coatis, and they also have two types of cone photopigments but a small number of cones. The last category is minimal color vision, where an organism has one type of cone pigment and relies on rod-cone interactions for wavelength discrimination; this is present in owl, monkeys, and raccoons (Breedlove and Watson 2017).

Development of Visual Perception

The development of the visual system is affected by the environment and experience. For example, the eyes of aquatic organisms are adapted to the lower light levels found in their niche (Berta et al. 2015). Ganges River dolphins (Platanista gangetica) have relatively poor eyesight as selection pressures associated with living in an opaque fluid have reduced the function of this cetacean’s eyes (Sinha and Kannan 2014).

It is essential for many organisms to have experiences with visual stimulation as a foundation for understanding what stimuli are available for the eyes and brain to process (Domjan and Grau 2015; Honigmann 1944; Troscianko et al. 2009). This is broadly outlined by the work of Gilbert Gottlieb (1976) who emphasized the role of experience in development. For example, human infants require a long period of locomotor experience for depth perception to be processed correctly, whereas other species, such as goats, do not require experience with movement to perceive depth (Adolph 2000). Stereoscopic vision in primates is fully dependent on experience shaping the timing and pattern of gene expression, as infant rhesus monkeys that have had their binocular vision impeded by prismatic lenses do not develop the excitatory binocular neurons necessary for normal binocular depth perception (Crawford et al. 1996).

Comparative Evolutionary Analysis in Visual Perception

The comparative study of visual perception, and especially its development, remains a poorly studied field and could shed light on the evolution of our own visual system (Shettleworth 2010). On the evolution of visual perception, the placement of an individual’s eyes can indicate the extent of binocular vision that is required by ecological factors such as the need to hunt (Shettleworth 2010). Such vision results in greater visual acuity in parts where there is overlap of the visual field (Clemente et al. 2010; Shettleworth 2010). For example, the Australian wolf spider’s (Lycosa leuckarti) eyes are positioned both anteriorly and posteriorly. Its overlapping binocular anterior and posterior medial eyes are used for distance judgment and prey capture and its non-overlapping posterior lateral eyes are used for long-range predator and prey detection (Clemente et al. 2010). In aquatic species like bottlenose dolphins (Tursiops truncatus) and goldfish (Carassius auratus), the eyes are positioned laterally, which allows them to potentially perceive a great deal around them but also allows them to view objects independently of the head on viewing angle since they can move three dimensionally and view the objects from different orientations (Cozzi et al. 2017). Consequently, bottlenose dolphins are able to move their eyes independently where one eye may look forward and dorsally, and the other eye may look rearward and ventrally (Cozzi et al. 2017). Evidence suggests that trilobites had some of the earliest eyes seen in the fossil record and because they contained a calcified cuticle, this structure was well-preserved. Not only was this an early eye, but it was likely a successful one as well, because this aquatic species maintained this visual system for about 270 million years (Clarkson et al. 2006). The likely visual field of the trilobite’s eye did not extend to objects above them since no predators or prey existed in that space at that time (Clarkson et al. 2006), giving a slightly angular look relative to the round eyes common in species today. Chitons have one of the more newly evolved eyes, characterized by aragonite-based lenses that allow their vision to operate in both air and water (Speiser et al. 2014). The convergent evolution of the trilobite and chiton mineral eyes show how they have both adapted to their similar environments in similar ways (Speiser et al. 2014).

Cross-References