CLASS A AND CLASS B OBSERVATIONS

This is true, for instance, in the case when three primary colors in an additive mixture of lights are adjusted to match a fourth one in a color match. When a match is achieved, two unequal physical stimuli lead to equal neural activity, and consequently to the same percept. Observations of matches or equalities, or of differences, and even thresholds, are methodologically simple, and they are not subject to the aforementioned ‘explanatory gap’ (p. 284). Brindley called such experiments ‘class A observations’. A conservative attitude towards psychophysics would require that one deals only with judgements such as these.

Observations that cannot be expressed simply as matches or thresholds are called ‘class B observations’. In such experiments the subject is required to describe the quality of his experience, for instance the hue of a light or its intensity. It is more difficult still to extract a common sensory aspect from two or more unequal qualities. Examples of such class B experiments might be comparing the brightness of differently colored lights, selecting colors of the same hue when saturation and/or lightness differs, or determining which stimuli have the same saturation when their hues and lightness are different. However, the ability to experience perceptual qualities and make class B observations is often a precondition for designing class A experiments. For instance, without the ability to distinguish colors along all qualitative dimensions, we would not be making color matches. Qualitative experience comes before its scientific exploration. The inner order and structure of perceived qualities will often give us an indication of how to understand the underlying physiological mechanisms. Without such clues, neurophysiologists would be lost when confronted with seemingly chaotic neural activity. Therefore, visual science cannot exclusively rely on class A experiments. To do so would mean to steer clear of many interesting phenomena and to declare class B type observations as off-limits to scientific inquiry. Both classes of experiments have a legitimate place in visual science, but we need to be aware of the fundamental difference between them.

Ideally, and whenever possible, psychophysical and electrophysiological experiments should be designed as class A experiments. Throughout this book, we have repeatedly discussed the problems that arise with class B experiments. Below we shall enter even deeper waters and describe interesting co-variations or analogies between simple physical properties of objects and the associated neural activity and perception. Analogies and correlates are not proofs of causation or interdependence, only a demonstration of a common structure. The study of such co-variations gives a broader basis for understanding the functional aspects of visual processes than would the isolated study of psychological, psychophysical or physiological relations or processes.

The interpretation of psychophysical results in terms of neural processes is fraught with caveats. However, it does not seem unreasonable to assume that the evolution of neural networks favors solutions taking best possible advantage of the high sensitivity of peripheral sensory receptors. This would imply that the early stages of sensory processing set the limits for detection. That being the case, one would expect to find that the behavioral sensitivity in various situations be traced back to the functional limits of receptors and retinal cells. At later stages of visual processing, higher visual

areas would add their particular flavors of perceptive features such as color and form

– qualities that come fully into play for supra-threshold stimuli.

B- and D-types of cells

ONand OFF-cells are first encountered in the retinal bipolar and ganglion cells. Earlier, when describing receptive field models in Figures 3.29 and 3.32, we discussed how ON-center cells, the Increment cells in our terminology, convey information about a stimulus becoming brighter, whereas OFF-center cells, or Decrement cells, signal the opposite, that a stimulus has become darker. In the context of ON-center/ OFF-surround and OFF-center/ON-surround systems in the cat, these two cell systems have been called B- and D-systems (Jung et al., 1952), where B stands for brightness and D for darkness. Below we shall take a further look at phenomena that gave rise to these labels (Spillmann, 1971; Magnussen, 1987).

The Hermann grid is shown at the top of in Figure 7.1. At the intersections of the black stripes in the top-left image, one can see diffuse bright spots, and at the intersections of the white stripes in the top right image, one sees dark shadows. The clarity of the illusion depends on the width of the stripes and can be modified by changing viewing distance or by fixating to the side of an intersection.

This illusion is thought to result from the joint activity of ON-center/OFF-surround and OFF-center/ON-surround cells [Figure 7.1(b)]. Take for instance an ON-center cell with its receptive field center placed at the intersection of two white stripes (right image). This cell is inhibited more by the surround than are other cells positioned elsewhere along the stripe away from an intersection (since a larger area of the surround is illuminated). Therefore an ON-center unit with its receptive field centered on the intersection will respond less vigorously than those centered elsewhere on a stripe. If ON-center units contribute to a brightness-coding system, the B-system, the former unit would signal ‘less bright’ than the latter, resulting in faint shadows in the intersections. For a particular ON-cell, angular size of the stimulus would be significant for the strength of the effect. As pattern elements grow, the illusion should be strengthened in the peripheral visual field since receptive field center size increases with retinal eccentricity. A similar argument holds for the OFF-center cells, the hypothetical darknessor D-system. Such cells would be activated more strongly in positions where the surround of the receptive field is illuminated more extensively, i.e. in the white intersections, and consequently the intersections would appear darker. B- and D-systems thus pull in the same direction, rendering the white intersections less bright, or darker than the adjoining stripes.

In the black line intersections (left) we see lighter spots, and, according to the same reasoning as above, B-cells are less inhibited at the black intersections than in a black stripe. Here too, the higher activity when the receptive field center is positioned on the black intersections signals brighter, and the smaller response of D-cells would

Figure 7.1 (a) The Hermann grid. In the black crossings one can see lighter spots, and in the white crossings darker spots. This phenomenon has been attributed to perceptive fields generated by ONand OFF-center cells as they form brightness and darkness systems. Brightness neurons (b; right) are more inhibited in the white crossing than along the white stripe because a greater part of the inhibitory receptive field surround is exposed to light. When placed in a black crossing, these cells are less inhibited by the white surround than when they are placed on a black stripe. This behavior is thought to correspond to the darker shades in the white crossings and lighter spots in the black crossings. The same argument, when applied to a darkness system with a reversed organization of the receptive field (b; left), leads to a similar result. Both systems are pulling in the direction of darker for the bright crossings and brighter for the black crossings. The strength of the effect is dependent on the size of the grid stripes in terms of visual angle.

pull in the same direction. ONand OFF-cells work in concert, but in principle the illusion can be explained in terms of either cell system alone, provided the receptive fields have spatially antagonistic centers and surrounds.

If this theory were correct, measuring the stripe width that gives the most conspicuous effect could indicate the size of the underlying ‘perceptive center fields’. Such fields would be made up of several cells with overlapping receptive fields and need not correspond to the receptive fields of single cells (Spillmann, 1971).

Contrast and contour enhancement

The interplay of activation and inhibition within a receptive field can accentuate a luminance gradient by enhancing the difference between two adjacent stimulus fields.

Figure 3.32 illustrates the responses of ONand OFF-center cells placed in different positions close to a luminance step. This example is for the cat. One of the classical examples of lateral inhibition leading to contour enhancement was found in the facet eye of the horse-shoe crab Limulus, as described by Hartline (1940), a Nobel Prize winner in 1967. Although the process is probably more complicated in the human visual system, lateral inhibition in the Limulus eye has long served as an example and a model of a biological contrast-enhancing mechanism (see p. 133).

Two juxtaposed areas of different colors, but with no luminance contrast, do not give rise to border enhancement in the same way that a pure luminance contrasts does. Chromatic Mach bands seem not to exist. Opponent cells with a center-surround antagonism in their receptive fields provide for a spatial response profile for achromatic borders that correspond to Mach bands. This is analogous to a bandpass filtering of the stimulus and is different from the mechanism described in Figures 3.32 and 3.33. There are other possible strategies for generating border effects similar to Mach bands, and we shall take a closer look at one interesting alternative that might apply to primates. A possible design for luminance border enhancement without concurrent enhancement of equiluminant chromatic borders is described in Figure 7.2.

In Figure 7.2(a) the responses of IL-M and IM-L cells to a moving border of achromatic luminance contrast and another of isoluminant red–green chrominance contrast are shown. Since both types of I-cells respond in the same way to the luminance contrast (upper left image), their summed response will be larger, roughly twice that of each cell system alone. In the case of the isoluminant red–green border (upper-right image), the responses of the two opponent I-cells are opposite; while IL- M cells are excited by red and inhibited by green, the reverse is true for IM-L cells. Taken alone, each of these two I-cells give a relatively smooth transition from one color to the other such as that shown in the upper-right drawing. Since activation is higher than inhibition, summation of the responses of the two I-units could provide information about brightness. On the other hand, a response difference of the two symmetric types of PC I-cells, where activation dominates over inhibition, would remove the luminance response in the achromatic case and extract two different chromatic dimensions (L–M and M–L; not shown in Figure 7.2).

Examples of opponent, PC D-cell responses to the same two border stimuli are given in Figure 7.2(b). Because of stronger inhibition in the D-cells, they have generally smaller responses than I-cells, and if they were mainly type II cells with coextensive center and surrounds, they would round off sharp contours and serve as low-pass filters for both luminance and chrominance contrasts.

In the physiological model of color processing that was presented in Figures 6.9 and 6.23, the activity of PC I- and PC D-cells of the same opponency were summated, a process that may occur in the blob clusters of area V1. Summation was considered necessary to preserve opponent responses over the whole range of luminance ratios for which we see color, from dark surfaces reflecting only a few percent of light to bright, self-luminous lights. A sum preserves and accentuates color differences

(bottom right image) over a larger luminance range than is possible with only one cell type alone. The sum of the band-pass and low-pass filters (of the PC I- and the PC D-cells) to the left in the figure removes the DC-level and enhances luminance contours.

As demonstrated earlier, this model of sums and differences of opponent cell responses, and other linear transformations of cell responses, account rather well for several aspects of color vision, especially the scaling of colors. One feature of this model is that it predicts contour enhancement equivalent to Mach bands for luminance contrasts, but none for chrominance differences. This agrees nicely with psychophysics. The model of Figure 7.2 is a little more complicated than that of Figure 3.32, but it explains the lack of chromatic Mach bands without the need for auxiliary hypotheses. The response magnitude of MC I-cells to borders would be much like the combined I þ D response of PC cells, as shown to the left of Figure 7.2(c), and MC D-cells would respond in the opposite phase, as shown in Figure 3.32. They are therefore both capable of adding to the achromatic border contrast. Thus, Mach bands to achromatic stimuli may well arise from activity of both PC and MC cells. Figure 7.3 shows the responses of monkey geniculate MC and PC cells to areas of different luminance and color, the ‘Mondrians’ (Land, 1983). Whereas MC cells are obviously more interested in the borders between colored areas, PC cells respond over the whole area and to several different colors. This difference is quite distinct in the response profiles below the Mondrians.

The receptive field of each cell scanned the Mondrian, and each spike of the response was imaged as a black dot on the monitor screen. This figure clearly illustrates the difference between these two cell systems; the transient response of MC-cells occurs only at the borders between the squares and rectangles, and it is up to the PC cells to ‘fill in the rectangles’ by responding inside the borders.

It should be noted that an enhancement of border contrast need not spread over a large area, but in some cases it does, as in the Cornsweet–Craik–O’Brien illusion (see for instance Jung, 1973). This, and similar phenomena have been described as due to some sort of ‘filling in process’. Historically, border enhancement and area contrast have been treated separately, and they have even been given their own names: Mach contrast (Mach bands) for the former and Hering contrast (Von Bekesy, 1968; Nobel Laureate, 1961) for the latter.

As we see from these figures, the responses of opponent PC cells are ambiguous, being influenced by changes in luminance, in color, and in the spatial and temporal parameters of the stimulus. In signal theory this is called multiplexing (MartinezOriegas, 1994). Only by comparing these responses with those of other, more or less specific cells, can the visual system arrive at an unequivocal judgement about the stimulus.