Department of Psychiatry, University of California, San Diego, CA 92093, USA
Bruce M. Dow, 3010 First Avenue, San Diego, CA 92103, USA. Email brudow{at}cox.net
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Abstract |
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Line Orientation |
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In the 1960s Hubel and Wiesel (1962,1968) made the discovery that the seemingly abstract concept line orientation was represented as a continuous variable in the primary visual cortex (striate cortex, area V1) of cats and monkeys. A recording microelectrode traversing the cortex parallel or nearly parallel to the surface encountered cells whose preferred orientation, designated numerically, changed linearly in relation to horizontal distance travelled by the electrode. Hubel and Wiesel (1974,1977) illustrated this phenomenon in the form of graphs of preferred line orientation versus horizontal distance through the cortical tissue (Fig. 1).
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Ocular Dominance |
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Using a reduced silver method, LeVay et al. (LeVay et al., 1975) demonstrated that the primary visual cortex in monkeys contained an orderly map of right and left eye dominance regions or columns (Fig. 2
). Physiological studies (Hubel and Wiesel, 1968
) suggested that the right/left eye segregation extended from the cortical surface to white matter, which was confirmed using a 2-deoxyglucose autoradiographic method (Kennedy et al., 1976
; Hubel et al., 1978
). The term column, derived from earlier work by Mountcastle (Mountcastle, 1957
) in the somatosensory cortex, carried with it the suggestion that columnar organization might be a basic property of the cerebral cortex in general. Hubel and Wiesel (Hubel and Wiesel, 1962
, 1963
, 1968
) also described the basic orientation unit as a column, though the linearity of the orientation change with horizontal distance (Fig. 1
) was suggestive of a continuous gradient.
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Orientation Column Model |
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Cytochrome Oxidase Blobs and Orientation Columns |
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The other two models in Figure 6, the E
and the A
, can also be ruled out by optical imaging studies, which showed that orientation singularities are mostly located in the middle of ocular dominance stripes (Bartfeld and Grinvald, 1992
; Obermayer and Blasdel, 1993
) and that adjacent singularities within the same ocular dominance column tend to have the same sign, with saddle points between them, while adjacent singularities across an ocular dominance column border tend to have opposite signs, with linear zones between them (Obermayer and Blasdel, 1993
). Linear zones in this context are two-dimensional patches, 0.51.0 mm across, within which iso-orientation lines remain roughly parallel to one another (Fig. 7
). Saddle points in this context are two-dimensional patches within which orientation preference remains approximately constant (Fig. 7
).
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The Oblique Effect |
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The oblique effect is not due to the optics of the eye (Campbell et al., 1966; Mitchell et al., 1967
). It is consistent with some single unit studies (Mansfield, 1974
; DeValois et al., 1982
; LeVay and Nelson, 1991
) and two brain imaging studies (Coppola et al., 1998
; Furmanski and Engel, 2000
) indicating more cells and more striate cortical tissue devoted to horizontal and vertical than other orientations. The effect is most prominent in central vision (Mansfield, 1974
; Berkley et al., 1975
).
The oblique effect suggests that the model in Figure 8A is preferable to the model in Figure 8B
. While there are studies that do not find the anisotropy for horizontal and vertical orientations in striate cortex (see LeVay and Nelson, 1991
), there are no studies reporting an anisotropy for diagonals.
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Color |
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Ewald Hering (Hering, 1920; Hurvich and Jameson, 1964
) proposed, on the basis of his own subjective impressions, that there appear to be four primary colors, red, yellow, green and blue, which function as two sets of opponent pairs. Hering displayed his primary colors in a circular fashion, with red opposite green and yellow opposite blue (Fig. 11
). As he noted, one can have a yellowish red (i.e. orange) or a bluish red (i.e. purple), but not a greenish red (or a reddish green). Hering also postulated a third opponent system, white and black, to account for luminance contrast effects. Hurvich and Jameson (Hurvich and Jameson, 1957
) developed Herings ideas into a quantitative psychophysical system (Hurvich, 1981
), providing for color opponency what Helmholtz had provided for trichromacy.
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Newtons color circle (Fig. 10) closes the spectrum; Herings color circle (Fig. 11
) introduces orthogonal opponent axes. Figure 12
combines Newtons and Herings color circles, depicting purple (at the left) as reddish blue, orange as yellowish red, lime as greenish yellow and aqua as bluish green. The named colors of Figure 12
are illustrated in Figure 13
.
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Extra-spectral Color |
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Color Opponency |
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Color opponency in the monkey visual cortex, using small spots and narrow bars as test stimuli to avoid encroachment on receptive field surrounds, was first reported by Hubel and Wiesel (Hubel and Wiesel, 1968), and subsequently confirmed by Dow and Gouras (Dow and Gouras, 1973
; Dow, 1974
; Gouras 1974
). Michael (Michael, 1981
) also reported finding color opponency in monkey visual cortex and presented data suggesting separate columnar systems for the opponent colors red and green, but not for yellow and blue.
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Cytochrome Oxidase Blobs and Color Columns |
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Livingstone and Hubel (Livingstone and Hubel, 1984) proposed that the cytochrome oxidase blobs constituted a system of non-oriented color columns interdigitated between mostly achromatic orientation columns. Their proposal implied that all colors would be represented within each blob column, though they did not present evidence on this issue.
Tso and Gilbert (Tso and Gilbert, 1988) conducted a study of blob columns and concluded that there were two types, one processing the opponent colors red and green, the other processing the opponent colors yellow and blue. They did not specify how cells with opposite color preferences would be situated within a single column.
Dow (Dow, 1974) noted the presence of non-oriented color cells in the upper layers of monkey visual cortex. Dow and Vautin (Dow and Vautin, 1987
) found two types of non-oriented upper layer zones, one containing mostly red cells, the other containing mostly blue cells. Yoshioka and Dow (Yoshioka and Dow, 1996
) documented the non-oriented upper layer zones as cytochrome oxidase blobs, proposing that there were two kinds of cytochrome oxidase blobs, red blobs and blue blobs.
Dow and Vautin (Dow and Vautin, 1987) noted the existence of many oriented color cells with preferences for colors toward the middle of the spectrum, such as orange, yellow, lime, green and aqua, and Yoshioka and Dow (Yoshioka and Dow, 1996
) showed that these oriented mid-spectral color cells were located in interblob regions. The results of the two studies led to the (initially) counterintuitive proposal that mid-spectral colors (i.e. yellow, lime, green) are more closely associated with orientation selectivity than end-spectral colors (i.e. red, purple, blue).
Psychophysical data support a mid-spectral/orientation association. Visual acuity is greater for mid-spectral than for end-spectral lines and gratings (Walls, 1943; Riggs, 1965
; LeGrand, 1967
; Kelton et al., 1978
; Mullen, 1987
). The yellow macular pigment, which selectively filters out blue light, assists in this process, along with the scarcity of blue cones in the foveal region of the retina (Wald, 1967
; Walls, 1967
; Williams et al., 1981
). Another contributing factor involves chromatic aberration and accommodation (Walls, 1943
, 1967
; Hartridge, 1947
; LeGrand, 1967
; Kruger et al., 1993
). In order to bring spectral light rays to a focus at the back of the retina, the lens must adjust its shape, a process known as accommodation. It is not possible to accommodate such that long and short wavelengths are both brought to a sharp focus on the retina. For standard viewing purposes, the accommodation mechanism selects the best compromise, which turns out to be optimal focus for middle wavelengths. Thus, red, blue and their mixture purple are generally defocused and associated with a certain degree of blurring. Mid-spectral images (yellow, lime, green) are better focused and associated with higher levels of visual acuity. Mid-spectral images are also typically associated with higher levels of luminance (Fig. 9
) and, on that basis, increased visual acuity (DeValois et al., 1974b
; Yoshioka and Dow, 1996
; Yoshioka et al., 1996
).
2-Deoxyglucose studies of Tootell et al. (Tootell et al., 1988a) showed a striking tendency for red and blue stimuli to label blobs more strongly than either yellow or green stimuli, supporting the concept of red and blue processing in blobs. Other studies (Lennie et al., 1990
; Leventhal et al., 1995
; Johnson et al., 2001
) did not find color cells restricted to blob regions, supporting the concept of color processing as a distributed function across the V1 cortical surface. Studies by Tootell et al. (Tootell et al., 1988b
), Silverman et al. (Silverman et al., 1989
) and Edwards et al. (Edwards et al., 1995
) indicated gradual rather than abrupt changes in contrast sensitivity and spatial frequency responses with increasing distance from cytochrome oxidase blob centers, supporting the notion of smooth gradients rather than distinct functional compartments in the macaque monkeys primary visual cortex. The possibility that spatial frequency may be represented as a continuous variable within the striate cortical tissue (Silverman et al., 1989
), while beyond the scope of the present discussion, is compatible with the model being presented here.
The results summarized above suggest that color may be mapped in continuous fashion across the surface of area V1, analogous to the continuous mapping of orientation. Cytochrome oxidase blobs, a discontinuity in the orientation map, serve an integral role in a continuous color map. A continuous color map has its own discontinuity, namely the interblob centers, which are achromatic (Dow and Vautin, 1987; Yoshioka and Dow, 1996
).
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Color Column Model |
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Based on perceptual considerations (Hurvich, 1981; DeValois and DeValois, 1993
; DeValois et al., 2000a
), roughly equal numbers of red and blue blobs would appear likely (see also Dow and Vautin, 1987
). The 2-deoxyglucose data of Tootell et al. (Tootell et al., 1988a
) do not indicate a preponderance of either red or blue blobs. Vautin and Dow (Vautin and Dow, 1985
) found roughly equal numbers of red and blue cells, using luminance matched stimuli; Yoshioka et al. (Yoshioka et al., 1996
), in the same laboratory, found fewer blue than red cells, using dimmer blue stimuli. Livingstone and Hubel (Livingstone and Hubel, 1984
) reported a preponderance of red cells in blobs, but their color testing was not systematic, often involving broad band filters without apparent luminance calibration, and they may have missed some blue cells. Tso and Gilbert (Tso and Gilbert, 1988
) reported twice as many red cells as blue cells in blobs (30 versus 15%), but they also used broad band filters and may have missed some blue cells. Optimal activation of blue cells requires narrow band filters to avoid inhibition from the middle wavelength-sensitive (M) cone system (Dow, 1974
; Gouras, 1974
).
The most likely place for the short wavelength-sensitive (S) cone system expansion (see above) reported by DeValois and colleagues in monkey striate cortex (Cottaris and DeValois, 1998; DeValois et al., 2000b
) is in the non-oriented blob regions, where the S cone system appears to be concentrated in striate cortex (Dow, 1974
; Dow and Vautin, 1987
; Tootell et al., 1988a
; Tso and Gilbert, 1988
; Yoshioka and Dow, 1996
) [for a comprehensive review see (Hendry and Reid, 2000
)].
There are three possible non-random arrangements of equal numbers of two types of blobs in a given small subregion of cortical tissue, namely alternating or stripes in two orientations (Fig. 14). Option B in Figure 14
would involve a right versus left eye color bias, which is clearly unacceptable. Option C in Figure 14
would have iso-color lines (e.g. blueblue, redred) running orthogonal to ocular dominance stripes, which seems undesirable, given that iso-orientation lines appear to run orthogonal to ocular dominance stripes, at least in linear zones (Obermayer and Blasdel, 1993
). For optimal matching of orientations and colors, one would like iso-color lines to run orthogonal to iso-orientation lines, i.e. parallel to ocular dominance stripes in linear zones. By exclusion, option A in Figure 14
is the most likely of the three.
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Figure 15A predicts that saddle points should be associated with either vertical or horizontal orientation and that diagonal orientations should be represented in the middle of linear zones. Figure 3
of Obermayer and Blasdel (Obermayer and Blasdel, 1993
) shows several saddle points, which appear to be associated with either horizontal or vertical orientations, and one linear zone, with a left oblique orientation in the middle.
The pinwheel color model is illustrated in Figure 15B. The interblob centers, indicated as empty circles, are achromatic singularities, with colors arranged as spokes. Spectral colors (see Fig. 12
), labeled ROYL (red, orange, yellow, lime) and BAGL (blue, aqua, green, lime), occupy the two lateral quadrants of each color circle. Extra-spectral colors, labeled B, pB, bP, P (blue, purplish blue, bluish purple, purple) and R, pR, rP, P (red, purplish red, reddish purple, purple), occupy the upper and lower quadrants of each circle. Spectral colors occupy the (binocular) regions near OD column boundaries, with mid-spectral lime at the actual boundary. Extra-spectral colors occupy the middle (monocular) portions of each OD column. As mentioned above, mid-spectral colors are more suitable for precise binocularity mechanisms, due to the higher visual acuity associated with them. According to the model, the middle portions of OD columns combine inputs from the two ends of the spectrum, while the border zones combine inputs from the two eyes. The notion of closing the ends of the spectrum to create extra-spectral colors was originally formulated by Isaac Newton (Newton, 1704
; MacAdam, 1970
).
Interblob center regions are the likely sites for processing of luminance, including the achromatic colors white, gray and black (Dow and Vautin, 1987; Yoshioka and Dow, 1996
; Yoshioka et al., 1996
), the particular achromatic color depending on relative luminance in comparison to nearby interblob centers, i.e. a given interblob center would function as white if local interblob firing rates were lower, black if local interblob firing rates were higher and gray if local interblob firing rates were the same.
Superimposition of Figure 15A,B indicates that spectral iso-color lines run roughly orthogonal to iso-orientation lines in linear zones (Obermayer and Blasdel, 1993
), which is appealing for the purposes of information storage and retrieval. Orthogonality would permit each color to be separately matched with all orientations and each orientation to be separately matched with all colors. The positioning of the lines could be adjusted so as to optimize orthogonality.
The association of vertical and horizontal orientations with color singularities (i.e. achromacy) in Figure 15 is a prediction of the model and may be related to the oblique effect mentioned earlier. This particular association should be testable using either psychophysical or biological techniques.
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Color Opponency Model |
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Color opponency is present in selected cells of area V1 (Hubel and Wiesel, 1968; Dow and Gouras, 1973
; Dow, 1974
; Gouras, 1974
; Michael 1981
; Livingstone and Hubel, 1984
; Vautin and Dow, 1985
; Tso and Gilbert, 1988
), but full perceptual color opponency may be deferred to a higher level of visual processing. Area V2, on the basis of its known anatomical and functional organization (Hubel and Livingstone, 1987
; Tootell and Hamilton, 1989
; Yoshioka and Dow, 1996
; Kiper et al., 1997
; Tso et al., 2001
), appears to offer a better geometry for color opponency (B.M. Dow, in preparation).
A particular problem for color opponency in V1, according to the present scheme, is that two of the primary colors, red and blue, are represented by mostly non-oriented and monocular cells, while the other two primary colors, green and yellow, are represented by mostly oriented and binocular cells. In V2, with some rearranging, this apparent incompatibility may be corrected. The recent study of Tso et al. (Tso et al., 2001), showing interactions between color and disparity zones in area V2, provides insight into the rearranging process. Incidentally, it should be noted that the end-spectral/mid-spectral, non-oriented/oriented distinction reported by our laboratory (Dow and Vautin, 1987
; Yoshioka and Dow, 1996
; Yoshioka et al., 1996
) is based on awake monkey recordings with full binocularity (and active fixation). Results obtained in anesthetized monkeys with monocular testing (or uncorrected binocular disparity) might be different.
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Summary and Conclusions |
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The model suggests that orientation singularities coincide with cytochrome oxidase blobs. Optical imaging researchers (Bartfeld and Grinvald, 1992; Blasdel, 1992
) have pointed out that this is not always the case. However, it should be noted that orientation singularities are identified in living tissue, while cytochrome oxidase blob locations are determined post-mortem, following tissue perfusion and fixation. Uneven tissue shrinkage could account for some of the discrepancies. A second possible source of error is pressure on the living brain tissue from the optical imaging apparatus (and a recording microelectrode, if one is used). A third possible source of error is from vascular pulsations, which may cause movement of the tissue during imaging. The bottom line is that one is dealing here with a living, pulsating, chemically sensitive tissue. It is inevitable that there will be deviations from perfect matching of pre-mortem physiology and post-mortem anatomy.
The model is testable. Blasdel and colleagues (Blasdel and Salama 1986; Blasdel, 1992
; Obermayer and Blasdel, 1993
) have used line orientations to look at voltage-sensitive dye activation patterns in monkey striate cortex. Presumably their studies could be repeated using colored gratings, similar to the stimuli used by Tootell et al. (Tootell et al., 1988a
) in their 2-deoxyglucose studies. Functional magnetic resonance imaging (fMRI) techniques, such as have been used extensively in humans, may be adaptable to monkeys as well (Logothetis et al., 1999
, 2001
) and fMRI resolution may now permit visualization of cortical columns (Grinvald et al., 2000
; Kim et al., 2000
).
Combining microelectrode recording with optical imaging (Tso et al., 2001) can be particularly valuable, with optical imaging results being used to guide microelectrode placement and microelectrode recording results being used to verify optical imaging data. Arrays of multiple electrodes (Eckhorn et al., 1988
) may be useful in columnar mapping studies. An advantage of microelectrode recordings, whether individual or multiple, is that one can sample different depths within the same column and document actual columnar architecture (Hubel and Wiesel, 1968
; Dow and Vautin, 1987
; Eckhorn et al., 1988
; Tso and Gilbert, 1988
; Yoshioka and Dow, 1996
; Tso et al., 2001
), including the possibility of columnar differences in the deeper layers of striate cortex (Bauer et al., 1980
, 1983
). Optical reflectance methods sample only the upper layers of cortex.
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Acknowledgments |
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