Ординатура / Офтальмология / Английские материалы / Seeing_De Valois_2000

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chromatic variations. A spectral sensitivity measure that shows linear additivity would also be useful. Such a linear measure, however, does not necessarily correspond to any or all perceptual intensity dimensions.

The human visual system, like all photosensitive biological systems, is not equally sensitive to increments and decrements of light from di erent spectral regions. Under photopic conditions, we are most sensitive to light in the midspectral region from 500–600 nm, with sensitivity falling o towards both spectral extremes. Spectral sensitivity under scotopic (dim-light) conditions is invariant and reflects the spectral absorption characteristics of the rods, which are the sole functioning receptors at these low light levels. However, the shape of the spectral sensitivity function at photopic levels, when multiple cone types are involved, depends on how it is measured; that is, the contribution of the di erent cone types to the intensive measure depends on the visual task involved.

There are several ways of comparing the e ective intensities of light of di erent wavelengths that yield linear additivity for lights of any spectral distribution. The most widely used of these is heterochromatic flicker photometry, which takes advantage of the fact that our ability to resolve rapid temporal changes in color is decidedly inferior to our ability to follow rapid changes in intensity. If one rapidly alternates two lights (at, say, 15 Hz) in the same location, a significant luminance di erence between the two will be visible and will appear as a brightness flicker. Any change in hue, however—even one as dramatic as an alternation between red and green—will be invisible. The two hues will blend, and the observer will perceive their additive mixture color (generally yellow or white in the case of red-green flicker). Under these conditions an observer can now adjust the intensity of one of the two flickering lights until the perception of brightness flicker is minimized. If various monochromatic lights are flickered against a standard white light in this way, a spectral sensitivity curve that has the property of additivity will be obtained.

A linearly additive measure of spectral sensitivity can also be derived from the minimally distinct border technique (Boynton & Kaiser, 1968). Subjects are presented with a bipartite field in which the radiance of one half is fixed. The subject controls the radiance of the test light in the other half field, and the two halves abut. The subject is asked to adjust the test radiance until the border between the two appears minimally distinct. At that point, the two lights will be equated in e ective intensity, and the equation will be identical to that determined by flicker photometry for the same two lights.

The CIE combined data from multiple laboratories to arrive at a standardized, linear, e ective intensity measure for the standard observer, o cially called a spectral luminous e ciency function, abbreviated V . (As there are individual di erences between normal observers in photopigments and in lens and macular pigmentation, for visual studies in which it is crucial to have isoluminant stimuli, one should determine the e ective luminance for the particular observer being tested. Such a measure is referred to as sensation luminance [Kaiser, 1988], to di erentiate

it from luminous e ciency for the standard observer.) Luminous e ciency is highest for wavelengths at about 555 nm and falls o rapidly at both longer and shorter wavelengths. If luminance were only a convenient engineering measure, it would have little relevance to visual perception, but it is more than that. It can be modeled very well as a sum of the spectral absorption curves of the L and M cone pigments (Vos & Walraven, 1971; Smith & Pokorny, 1975; Schnapf et al,. 1988). The luminosity function is also well fit by the sum of the outputs of the spectrally nonopponent LGN cells (De Valois et al., 1966; Lee, Martin, & Valberg, 1988*), indicating that the cells in the Mc path are computing this sum of L M.

A quite di erent intensity measure from luminous e ciency, although sometimes confused with it, is brightness. This is a perceptual measure determined by having an observer adjust two lights until they appear equally bright. Similar spectral sensitivity curves are obtained for the increment threshold for large, long-dura- tion monochromatic lights presented on a white background (Sperling & Harwerth, 1971). For any given light under invariant viewing conditions, brightness varies monotonically with luminance, but lights of di erent wavelengths equated in luminance are by no means necessarily equal in brightness. For example, monochromatic lights near the spectral extremes typically appear much brighter than midspectral monochromatic lights of the same luminance. Also, spectrally complex lights containing multiple wavelengths typically appear less bright than monochromatic lights equated for luminance, the Helmholtz-Kohlrausch e ect. The failure of additivity is such that the sum of two monochromatic lights can even appear to be less bright than one of the separate lights alone (Guth, 1967).

The spectral brightness function is typically three-humped, with highest sensitivity in the regions of 430, 540, and 630 nm, as opposed to the single region of highest luminance at about 555 nm. These three regions of highest brightness correspond closely to the regions of peak responses from S LM, M L, and M opponent LGN cells to incremental flashes of monochromatic light. Although only the nonopponent cells contribute to luminance, brightness appears to be contributed to by all the LGN cells, both opponent and nonopponent (Abramov, 1968; Sperling & Harwerth, 1971).

B. Spatial Contrast Sensitivity

To the extent that the visual system behaves linearly, the detectability of any spatial pattern can be predicted from knowledge of the observer’s spatial contrast sensitivity function (CSF). A discussion of such an approach to spatial vision can be found in De Valois and De Valois (1988) and in Geisler and Albrecht (chapter 3, this volume). Although an infinite number of possible basis functions could be used to measure an observer’s CSF, the most common is a grating pattern that various sinusoidally in one spatial dimension while remaining invariant in the orthogonal dimension. The experimenter determines the minimum contrast that an observer

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can detect at a particular spatial frequency, defined in terms of cycles per degree visual angle (c/deg).The grating pattern can vary either in luminance contrast (e.g., a black-white grating) or in color contrast (e.g., a red-green grating).

The foveal spatial CSF for luminance-varying gratings measured at photopic light levels is bandpass. Contrast sensitivity is greatest for spatial frequencies of about 2–4 c/deg, with reduced sensitivity to both higher and lower spatial frequencies. When spatial frequency is represented on a logarithmic scale, as it usually is, the fallo in sensitivity is quite rapid and pronounced at the higher spatial frequencies, and more gradual in the low spatial frequencies.

To make comparable measures for color-varying patterns that contain no luminance variation is di cult. In theory, such a pattern can be produced by adding together two colored luminance-varying patterns out of phase (e.g., a red luminance grating interlaced with a green luminance grating to produce a red-green color grating). If the two are matched in space-averaged luminance and in luminance contrast, then their superposition should produce an isoluminant color-vary- ing sinusoid. However, chromatic aberration produced by the eye’s optics tends to produce luminance artifacts in the retinal image of such a pattern. (See Thiros, chapter 1, this volume, for a discussion of chromatic aberration.) Although there are ways to minimize the e ects of these unintended luminance variations, it is probably wise never to assume that a retinal image is truly isoluminant. Luminance artifacts are a particular problem because of the great sensitivity of the visual system for even miniscule amounts of luminance contrast. Nevertheless, the di erences that are seen when comparing spatial CSFs for luminance-varying patterns with those for nominally isoluminant patterns suggest that standard methods of producing isoluminant stimuli are at least reasonably adequate at low-to-middle spatial frequencies. Because the problem of chromatic aberration grows increasingly severe as spatial frequency increases, measurements made with higher frequencies become increasingly problematic.

A second problem arises in comparing contrast sensitivity for luminance and chromatic patterns, namely, the choice of a contrast metric. Many have been used, though they have often been selected out of expediency, not principle. For the current discussion, it is su cient to note that all such metrics should be simply related, and the only one that provides an obvious point of comparison with luminance contrast metrics is that of cone contrast (Cole & Hine, 1992), which is derived by calculating the variation in light absorptions in each of the cone classes. Most studies of chromatic spatial contrast sensitivity have used other simple but less satisfactory measures of contrast. For example, the contrast of a red–green isoluminant grating can be defined as being equivalent to the luminance contrast of either the red or the green component gratings alone.

When the test pattern is a set of isoluminant red–green sinusoids of di erent spatial frequencies, the foveal spatial contrast sensitivity function of a normal observer is low-pass, not band-pass as it is for luminance. Sensitivity either continues to increase as the spatial frequency of the test becomes increasingly lower, or it

reaches an asymptote at some low spatial frequency (van der Horst & Bouman, 1969; van der Horst, de Weert, & Bouman, 1967; Kelly, 1983; Granger & Heurtley, 1973; Mullen, 1985). At higher spatial frequencies, contrast sensitivity falls quite rapidly, not extending to the high frequencies that are readily seen when the test grating is defined by luminance variations.

The implication of the di erences between the luminance and the chromatic CSFs is that color di erences alone, in the absence of corresponding luminance variations, cannot support fine spatial acuity. In a red–green world without luminance variations, for example, written material would have to be printed in much larger letters, and the fine resolution to which we are normally accustomed (which reflects sensitivity to luminance-varying patterns) would not exist.

Spatial resolution is even more severely compromised when the test pattern produces di erential absorption only in the S cones (a tritanopic confusion axis, the 90 –270 axis in MBDKL space). S cones alone cannot support spatial discriminations as good as those achieved by the LM cone mosaic, because they are so few in number and so widely spaced on the retina. Several attempts have been made to measure the spatial contrast sensitivity function using stimuli that are restricted to the S cones (e.g., Cavonius & Estévez, 1975; Green, 1972). In general, researchers agree that contrast sensitivity for S-cone-isolating gratings begins to fall once the spatial frequency exceeds 1 c/deg, and the ability to resolve gratings disappears for patterns higher than about 10 c/deg.

Although the decision as to how to compare absolute contrast sensitivity for luminance versus chromatic patterns is somewhat arbitrary, a comparison of the shapes of their respective CSFs is straightforward. At low temporal frequencies, as usually measured, the spatial CSF for luminance is bandpass, with considerable high-spa- tial-frequency and some low-spatial-frequency attenuation. The color CSF, on the other hand, is low-pass, with little or no low-frequency attenuation (at least down to very low spatial frequencies). This can be understood in the di ering ways that Pc LGN cells, which multiplex color and luminance information, respond to chromatic versus luminance variations, respectively (De Valois & De Valois, 1975; De Valois et al., 1977). Information about very high spatial frequencies is lost due to optical imperfections and the finite spacing of the photoreceptors (see De Valois & De Valois, 1988, for discussion). This is reflected in the high-frequency attenuation of both the color and the luminance CSFs. However, information about low spatial frequencies is not lost due to either the eye’s optics or the receptor spacing, but rather results from inhibitory lateral neural interactions.

For low spatial frequency patterns, which produce fairly uniform illumination across the entire RF of a retinal or geniculate Pc cell, the center and surround regions are antagonistic for luminance variations, but synergistic for chromatic variations.Thus LGN cells show decreased sensitivity to low spatial frequency luminance variations, but increased sensitivity to low spatial frequency color variations. Perhaps the easiest way to understand this is to consider that an intensity change drives the L and M cones in the same direction, but a color change drives them in oppo-

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site directions; however, L and M cone outputs are combined in Pc LGN cells in an opponent way. A uniform luminance increment, then, would result in an excitatory input from the L cones and an inhibitory input from the M cones to a L M cell, and thus little total response. But a color change toward long wavelengths would produce excitation from L cones and a decrease in inhibition from M cones. The combination would therefore produce a large response.

C. Temporal Contrast Sensitivity

A moving or flickering pattern produces a temporal change in light in a given retinal area. One can ask how sensitive we are to di erent temporal frequencies (speci- fied in Hz cycles per second) of color changes versus luminance changes. Historically, the temporal sensitivity of the chromatic system has been assessed using a homogeneous flickering field alternating in time between two di erent colors.That of the luminance system has been studied using a black–white flickering stimulus. When the flicker modulation depth (i.e., the amplitude of the chromatic or luminance di erence between the two) is held constant and the flicker frequency is varied until the flicker can no longer be seen, the measure is referred to as the critical flicker frequency (CFF). The CFF depends upon such factors as mean luminance and stimulus size, but when the two stimuli that are alternated are chromatic stimuli equated for luminance, the CFF will rarely exceed 12–14 Hz. This stands in marked contrast to the CFF for luminance variations, which may easily reach 60 Hz or higher under photopic conditions.

Temporal contrast sensitivity measures can be used (assuming linearity) to derive temporal impulse response functions for color and luminance, an estimate of the temporal response sequence that follows a single brief stimulus impulse. For an increment in luminance at a photopic adaptation level (90 cd/m2, for instance), the derived temporal impulse response function is biphasic, with an excitatory response that peaks at about 40 ms, drops to zero by about 70 ms, then becomes negative, returning to the baseline only after 170 ms or so. At the same luminance level, however, the derived temporal impulse response function for an isoluminant color change is monophasic. It reaches its positive peak only after approximately 70 ms, has no negative lobe, and falls slowly to zero after 250 ms or so (Swanson, Ueno, Smith, & Pokorny, 1987). These di erent impulse-response functions for color and luminance appear to be directly related to the di erent temporal properties of cells in the Pc and Mc paths. Macaque Pc cells produce monophasic temporal responses to a flash of light, whereas Mc cells give quite biphasic temporal responses (Schiller & Malpeli, 1978).

Another way to characterize the temporal properties of the visual system is to examine sensitivity to stimuli varying sinusoidally in time. For stimuli of very low spatial frequencies or for uniform illumination, the temporal CSF functions for luminance and for color are very similar to their respective spatial CSFs, bandpass

for luminance, and low-pass for color.Very high temporal frequency attenuation for both color and luminance patterns is primarily attributable to the random di usion characteristics of the intrareceptor cascade intervening between the capture of a photon of light and the initiation of a change in permeability of the receptor outer membrane. Synaptic neural processes also contribute to this loss in high temporal frequency information, since the highest temporal frequencies to which cells respond decrease at each successive synaptic level. These processes decrease sensitivity to high temporal frequencies for both luminance and color. Low temporal frequency attenuation, which is seen for luminance but not color variations, must have a di erent explanation, perhaps in the di erential latency of the RF center versus surround inputs to ganglion and LGN cells. As in the case of the di erence between luminance and color spatial CSF functions, the presence of low-temporal-fre- quency attenuation for luminance but not color can be explained by the opposite changes in receptor output produced by variations in intensity versus color.

For very low temporal and spatial frequencies, the RF center and surround inputs to a Pc LGN cell are antagonistic for luminance patterns and synergistic for color patterns, as discussed above. At such low temporal frequencies, the slightly longer latency of the surround relative to the center is an insignificant proportion of a total cycle, and the center and surround would essentially coincide in time. However, as the temporal frequency increases, the fixed center/surround latency di erence would increasingly shift the relative phases of the center and surround until at some temporal frequency they would be out of phase rather than in phase. At this higher temporal frequency, center and surround would now be synergistic for luminance and antagonistic for color. Luminance sensitivity thus increases while sensitivity to color decreases with increasing temporal frequency up to a point, so that the luminance temporal CSF is bandpass whereas the color temporal CSF is low pass.

D. Color Vision Defects

Approximately 8% of males and 1% of females di er significantly from the majority of the population in their color vision abilities. A very small proportion of these, called monochromats, can make no discriminations based solely on spectral di erences. They are truly color blind. Most of these are rod monochromats, who appear to have no functioning cones or to be incapable of using whatever signals their cones might provide. A larger (but still small) group of observers are dichromats. They can match any light with a combination of only two primaries, unlike the normal observer who requires three primaries to match many test lights. Dichromats appear to lack one of the three basic classes of cones and are classified in terms of which cone type is believed to be missing. Protanopes are missing their L cones, deuteranopes their M cones, and tritanopes their S cones. Their spectral sensitivity, wavelength discrimination, and other color vision functions di er in ways that are predictable from the loss of one cone type. The most dramatic di erence from normal

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trichromats in the visual capabilities of the various classes of dichromats is that each has a narrow spectral region (known as a neutral point) in which even a monochromatic light cannot be discriminated from white.

The third and most common class of color vision anomalies occurs in observers who are trichromatic, like the majority of the population, but make color matches that may di er quite dramatically from those a “normal” trichromat would set. Anomalous trichromats, like dichromats, are classified by the cone system that appears to be a ected. Thus, there are protanomalous, deuteranomalous, and tritanomalous observers. Anomalous trichromats appear to have a cone class that contains a photopigment di erent in its spectral absorption function from that found in normal trichromats (Neitz & Neitz, 1998).

IV. COLOR APPEARANCE AND ITS PHYSIOLOGICAL BASES

The various discrimination functions described above all reflect the degree to which an observer can tell that two stimuli di er along some specified dimension. They do not represent the appearance of stimuli, except in the most minimal sense of the distinction between “same” and “di erent.” As Hering realized, however, an understanding of color vision must encompass the more complex aspects of color appearance, as well as color discriminations.

A. Opponency

Following the early suggestions of trichromacy from Palmer (1777) and Thomas Young (1802), its quantitative demonstration by Maxwell (1860), and Helmholtz’s popularization and extension (1867) of Young’s theory, the nature of color mixture and its explanation formed the central topic in the study of color vision. The work of Ewald Hering (1878) helped shift scientific concern back to the perceptual appearance of color, not just the discrimination and matching of colors. Hering noted that among the chromatic hues (here ignoring the achromatic range of blacks, whites, and greys), four hues, red, green, blue, and yellow, are perceptually unique. Each of them exists in a pure form that appears to contain no tinge of any other hue, unlike the intermediate or mixture colors such as purple (which appears to contain both red and blue), cyan (which appears to contain both blue and green), or orange (which appears to contain both red and yellow). Further, he noted, the unique hues exist in two opponent pairs that have a special, mutually exclusive relationship. Red and green, Hering said, cannot be seen in the same place at the same time. Though there are reddish blues and reddish yellows, there is no reddish green or greenish red. Similarly, blue and yellow are an opponent pair. Chromatic opponency provides a useful framework within which to consider complementary colors (two colors that, when added in proper proportions, combine to produce an achromatic white or grey), negative afterimages, and the Bezold-Brücke E ect (a

change in hue produced by a change in the luminance of a monochromatic light), among other phenomena.

Quantification of the spectral response functions associated with the four unique hues identified by Hering awaited the development by Jameson and Hurvich (1955, 1956; Hurvich & Jameson, 1955, 1956) of a psychophysical hue cancellation technique. In this procedure, a subject is presented with a sequence of test lights of various wavelengths and told to cancel or eliminate all the greenness, say, by adding an appropriate amount of red to the test light.This method exploits the opponent relationship between, in this case, red and green, and allows one to define precisely the extent to which a given unique hue contributes to the percept of various nonunique hues. As Hering’s analysis would predict, and Jameson and Hurvich demonstrated, the addition of red can completely cancel the appearance of green in any stimulus over the whole range of wavelengths that have any greenish appearance. With the red and the green canceling each other out, the test light will now appear blue, yellow, or achromatic. Similarly, the addition of blue can completely cancel the appearance of yellow, and vice versa, leaving the test light appearing red, green, or achromatic. When the unique hue spectral response functions (or chromatic valence functions) for monochromatic lights are defined by the color cancellation method, red, which is most prominent in the long wavelengths, is seen also at the very short wavelengths. This reappearance of red poses a challenge to physiological models of color encoding and will be discussed further below.

The work of Hurvich and Jameson forced a serious reexamination of color models based on independent paths from three cones to the brain. Zone models (which typically begin with a trichromatic initial stage followed by one or more opponent interaction stages) were initially proposed more than a century ago (e.g., von Kries, 1905). However, it was the work of Hurvich and Jameson along with the supporting physiological evidence from LGN recordings in the monkey that brought them to the fore in modern studies of color vision. Thus, the observations of Young and Helmholtz, on one hand, and those of Hering, on the other, are not mutually contradictory as they were once thought to be; rather, they reflect di erent stages in the processing of color by the visual system.

B. Hue

Color has three main perceptual dimensions (surface colors can also have such perceptual properties as luster). Hue is the term used for the dimension described in casual conversation by names such as red, yellow, green, and purple. The physical variable that corresponds most closely to the dimension of hue is wavelength for a monochromatic light. The wavelengths that we see as light form a continuum from about 400 to 700 nm, and the peak sensitivities of the cone photopigments are at about 430, 530, and 560 nm. One might well expect, therefore, that the colors we perceive in the spectrum would be arranged in a line across the spectrum, with the

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hue of the shortest wavelengths being most di erent from that of the longest wavelengths. That is not the case; rather, the shortest and longest visible wavelengths resemble each other, and the perceptual arrangement of the colors is not onedimensional, along a line, but two-dimensional, as if around a circle. Related to this is the fact that certain colors are complementary, so that when added together their hues cancel, producing an achromatic color.

The fact that colors form a circle has been known at least from the time of Newton, but the explanation for it was not obvious. A Helmholzian organization, with three color receptors feeding separately to the brain, would lead to a one-di- mensional, linear arrangement of the di erent hues. That hues instead appear to be organized as a circle reflects the fact that the receptor outputs are not separately projected but rather compared in two opponent organizations. The initial opponentcolor organization, as we have seen, is between cone types in the retina, L versus M, and S versus L M. At the striate cortex there is a further interaction in which the outputs of the S-opponent cells are combined with that of the LM opponent cells (Cottaris & De Valois, 1998).The color system related to the very longest wavelengths (specifying red) thus also receives an input from receptors sensitive to the very shortest wavelengths, and the system specifying blue receives input both from the receptors sensitive to the shortest and from those sensitive to the longest wavelengths.

Many studies have determined how hue varies as a function of the wavelength of monochromatic light (e.g., Abramov, Gordon, & Chan, 1990; Sternheim & Boynton, 1966; Werner & Wooten, 1979), using a hue-scaling procedure. The observer is typically asked to scale the hue of each monochromatic light in terms of how much red, yellow, green, or blue she or he perceives in it.These studies agree in finding that the very long wavelengths are reported to be predominantly red, often with a small admixture of yellow. The red shades into a more equal mixture of red and yellow, eventually becoming uniquely yellow at wavelengths around 575–585 nm, then yellow-green at still shorter wavelengths. The spectral region identified as uniquely green varies considerably across studies and among subjects, ranging from about 500 nm to 525 nm. As the wavelength is lowered further, green becomes green-blue and finally unique blue, which appears for most subjects at about 475–480 nm. Lights of still shorter wavelengths are perceived as a combination of blue and red. To produce a color that is identified as unique red, it is usually necessary to add short-wavelength light to a long wavelength, producing an extraspectral color.

To compare the hues of di erent stimuli directly with the underlying cone, LGN opponent cell, and striate cortex cell responses, De Valois, De Valois, Switkes, and Mahon (1997) had observers scale the hues of the same isoluminant stimuli that had been used in single-cell recording experiments. The results (see Figure 9) show clearly that the hues seen as red, yellow, green, and blue do not coincide with the outputs of the various LGN opponent cell types, but are in each case rotated in MBDKL color space o these axes. This rotation was predicted by the De Valois

FIGURE 9 Scaling of the color appearance of various isoluminant stimuli. Plotted for each color vector is the percentage of times that the given stimulus was called each of the four permissible color names, red (R), yellow (Y), green (G), or blue (B). If the color names directly reflected the lateral geniculate nucleus (LGN) cell responses shown in Figure 5, B would coincide with S (90 ), G with M-L (180 ), and so forth. Note that the way in which the perceptual responses are shifted from the geniculate axes is as predicted to occur with a further stage of color processing by the De Valois and De Valois (1993) color model.

and De Valois (1993) model, and is accounted for by the combination at the striate cortex of inputs from the LM-opponent and the S-opponent cells to form the various primary hue systems. Most striate cells are found to receive inputs from all the di erent LGN opponent cell types, just as was postulated (De Valois, Cottaris, & Elfar, 1997).

One might suppose that the colored lights that we describe as, say, red, simply reflect the way in which we had been taught to use the English term “red.” Our breaking up color space into di erent hues could just reflect a linguistic convention rather than any underlying physiological property of the visual system. However, the evidence suggests otherwise. Extensive studies of the color categorization of people of many di erent languages and cultures (Berlin & Kay, 1969; Kay, Berlin, Ma , & Merrifield, 1997) show a surprising agreement in how they divide up the colors into di erent hue categories. In some languages there are only words for light and dark, but if there are specific hue terms in the language, the color regions covered by particular color terms agree very closely with ours. Thus if asked to sort multiple colored chips into di erent color categories, people across dozens of di erent languages (even among isolated tribes in New Guinea, for instance) will group together in one category all the chips that we see as reddish, and will identify as the best exemplar of that color the same chip that we might describe as unique red.

C. Saturation

The second chromatic perceptual dimension, saturation, refers to the degree to which a given stimulus di ers from achromatic. It describes the amount of color