K. L. Gunther
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Non-cardinal color mechanism strength differs across color planes but not across subjects Karen L. Gunther Psychology Department, Wabash College, 301 West Wabash Avenue, Crawfordsville, Indiana 47933, USA ([email protected]) Received September 5, 2013; revised December 20, 2013; accepted January 13, 2014; posted January 14, 2014 (Doc. ID 196918); published February 25, 2014 This study tested two hypotheses: (1) that non-cardinal color mechanisms may be due to individual differences: some subjects have them (or have stronger ones), while other subjects do not; and (2) that non-cardinal mechanisms may be stronger in the isoluminant plane of color space than in the two planes with luminance. Five to six subjects per color plane were tested on three psychophysical paradigms: adaptation, noise masking, and plaid coherence. There were no consistent individual differences in non-cardinal mechanism strength across the three paradigms. In group-averaged data, non-cardinal mechanisms appear to be weaker in the two planes with luminance than in the isoluminant plane. © 2014 Optical Society of America OCIS codes: (330.0330) Vision, color, and visual optics; (330.1720) Color vision; (330.5510) Psychophysics; (330.7320) Vision adaptation. http://dx.doi.org/10.1364/JOSAA.31.00A293
1. INTRODUCTION We know that retinal ganglion cells and neurons in the lateral geniculate nucleus (LGN) of the thalamus respond best to variations in black versus white [i.e., luminance (LUM)], reddish versus greenish (RG), and violet versus chartreuse [loosely bluish versus yellowish, i.e., tritan (TRIT)] [1–4]. These color pairings are known as the cardinal axes of color space because they define the axes of a three-dimensional color space (see Fig. 1). Colors beyond these, such as orange and turquoise, form the non-cardinal (or higher order) axes. Neural mechanisms underlying the perception of noncardinal colors have not been found in the retina or the LGN (other than possibly the S– cells of Tailby et al. [5]); thus they must arise in the cortex. (Note: by “mechanism” I mean a group of neurons tuned to respond to certain colors—see Gunther [6] for a more complete discussion of mechanisms.) Neurophysiological evidence for cortical non-cardinal mechanisms has been found. For example, Lennie et al. [7] and Tailby et al. [8] electrophysically recorded from macaque neurons and found that primary visual cortex (V1) neuronal preferences were spread throughout color space. In LGN, in contrast, neuronal preferences were clustered around the cardinal colors [7]. Similarly, Kiper et al. [9] found a wide range of color preferences for neurons in V2. Using principal components analysis, pattern classification, and idealized modeling of color tuning on functional magnetic resonance imaging (fMRI) data from human subjects, Brouwer and Heeger [10] found that color tuning in the isoluminant plane, including non-cardinal colors, was most robust in cortical areas V4 and VO1; good in V1, V2, and V3; and poor in LO1, LO2, V3A/B, and MT. Parkes et al. [11] found that the V1 fMRI response more clearly separated prototypical (not cardinal) red, green, blue, and yellow than it separated the 1084-7529/14/04A293-10$15.00/0
cardinal (i.e., LGN) colors. Using both electrophysiology and fMRI in macaques, Conway et al. [12] found neurons in and around V4 that were tuned to a wide array of colors. Psychophysical measurements can show if these noncardinal-preferring neurons are used for color vision. A variety of psychophysical techniques have been used to search for neural mechanisms underlying the non-cardinal colors, including adaptation [13–19], factor analysis [20], masking [21–27], plaid coherence [28–30], and visual search [6,31,32]. As can be seen in Table 1, the results have been mixed: several studies have found evidence for non-cardinal mechanisms, others have not, and still others have found their existence in some but not all subjects or in some but not all planes of color space. Note that the variability in results is not correlated with paradigm—it is not the case that masking always finds non-cardinal mechanisms while adaptation does not, for example. In his comprehensive review of the psychophysical non-cardinal literature, Eskew [33] concluded that “no consensus on higher order mechanisms has been reached” (p. 2686). A couple of solutions to this conundrum have been proposed. First, Eskew [33] proposed from his literature review, and Hansen and Gegenfurtner [27] empirically determined, that studies that plot colors in cone contrast space (e.g., [23,26]) tend to not find non-cardinal mechanisms, while those that use Derrington–Krauskopf–Lennie (DKL) color opponency space (Fig. 1) tend to find support (most of the rest of the references in Table 1). Second, Stoughton et al. [19], in macaques, found that gratings, which tap cortical neurons, reveal non-cardinal mechanisms, but full-field stimuli, which better stimulate LGN neurons, do not. However, studies where some but not all subjects exhibit non-cardinal mechanisms [16–18,25,28,34] cannot be explained by stimulus parameters or which color space is used. © 2014 Optical Society of America
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J. Opt. Soc. Am. A / Vol. 31, No. 4 / April 2014
K. L. Gunther
Fig. 1. DKL three-dimensional color space. Cone inputs are shown on axes: L, long-wavelength sensitive; M, medium-wavelength sensitive; S, short-wavelength sensitive. Reprinted from K. L. Gunther and K. R. Dobkins, “Independence of mechanisms tuned along cardinal and noncardinal axes of color space: evidence from factor analysis,” Vis. Res. 43, 683–696 (2003).[20]. Copyright 2003, with permission from Elsevier.
These inconsistent results, and the small sample sizes used, have led to the hypothesis that the existence of non-cardinal mechanisms may reflect individual differences [17,25,33,34,40]—some subjects may have them while others do not. The studies in Table 1 that support the existence of non-cardinal mechanisms may have obtained a lucky draw of all “non-cardinal subjects.” The studies that did not find evidence for non-cardinals may have drawn all subjects without non-cardinal mechanisms. The small sample sizes used in these studies would allow for skewed samples such as these. Some studies appear to have a mix of subject types [16–18,25,28,34]. Although the notion of individual differences has been suggested by others, and recently there has been increasing awareness that there is more variability across humans than had once been assumed, individual differences as an explanation for the discrepant noncardinal results has not yet been explored in depth across multiple paradigms.
Table 1. Review of the Literature on the Existence of Non-Cardinal Color Mechanismsa Reference Dobkins, Stoner, & Albright (1998) [28] Dobkins, Stoner, & Albright (1998) [28] D’Zmura (1991) [31] D’Zmura & Knoblauch (1998) [21] Eskew, Newton, & Giulianini (2001) [34] Flanagan, Cavanagh, & Favreau (1990) [35] Gegenfurtner & Kiper (1992) [22] Giesel, Hansen, & Gegenfurtner (2009) [36]
Giulianini & Eskew (1998) [23] Goda & Fujii (2001) [37] Gunther (2014) [6] Gunther & Dobkins (2003) [20] Hansen & Gegenfurtner (2006) [24] Hansen & Gegenfurtner (2013) [27] Kooi, DeValois, Switkes, & Grosof (1992) [29] Krauskopf & Gegenfurtner (1992) [13] Krauskopf, Williams, & Heeley (1982) [14] Krauskopf, Williams, Mandler, & Brown (1986) [15] Krauskopf, Williams, Mandler, & Brown (1986) [15] Krauskopf, Wu, and Farell (1996) [30] Li & Lennie (1997) [25] Mizokami, Paras, & Webster (2001) [16] Monnier & Nagy (2001) [32] Nagi, Neriani, & Young (2004) [38] Sankeralli & Mullen (1997) [26] Stoughton, Lafer-Sousa, Gagin, & Conway (2012) [19] Webster & Mollon (1991) [18] Webster & Mollon (1994) [17] Webster & Mollon (1994) [17] Zaidi & Halevy (1993) [39] a
Paradigm Plaid coherence unikinetic Plaid coherence bikinetic Visual search Masking Detection in noise Tilt aftereffect Noise masking Chromatic discrimination of variegated stimuli Masking Texture discrimination Visual search Factor analysis (n 41) Noise masking Noise masking Plaid coherence Adaptation Adaptation Adaptation Color discrimination and detection Plaid coherence Noise masking Adaptation Visual search Visual search Masking Adaptation Adaptation Adaptation, contrast detection Adaptation, reaction time Continuously changing colors
RG/TRIT Plane n
RG/LUM Plane n
TRIT/LUM Plane n
2/6,+ 4/6 weak 1/1 3/3 3/3 1/6 3/3 weak
3/3 weak 3/3
3/3 weak
4/4
0/3 4/4 10/10 + 3/3 No 5/5 10/10
10/10 + 3/3, all weak 10/10 + 3/3, all weak Yes Yes 4/4 Yes in 9 pooled subjects
1/1 weak 1 no, 1 weak 2/2 2/2 2/2 2/3 1 strong, 2 weak 3/3 5/5
0/2
Not shown
0/2 0/2
0/2 0/1
0/3 2/2 (monkeys) 2 strong, 2 weak 2/3
2/2 3/3 weak
Yes (n ?) 1 strong, 2 weak
2/2
1 weak
1 weak
2/2
Numbers represent the number of subjects demonstrating non-cardinal mechanisms out of the total number of subjects tested.
K. L. Gunther
This hypothesis of individual differences in the existence of non-cardinal mechanisms is tested here by searching for noncardinal mechanisms across three paradigms: adaptation, masking, and plaid coherence. I am unaware of any other studies that have used multiple paradigms to study the issue of individual differences in the existence of non-cardinal mechanisms. (Dobkins et al. [28] did measure both oculomotor responses and perceptual responses in the same subjects, but both to a plaid stimulus—multiple stimulus paradigms were not used. Likewise, Webster and Mollon [17] measured both contrast detection and reaction time in the same subjects, but both following adaptation. Neither study used multiple measures to explicitly examine individual differences.) By the multiple-paradigm method, if a given subject shows noncardinal mechanisms in one paradigm, he is predicted to do so in all three paradigms. If a different subject fails to show noncardinal mechanisms in one paradigm, he is predicted to not show them in any paradigm. A second aspect that was examined in this study is whether non-cardinal mechanisms exist in all three planes of color space or only in the isoluminant (RG/TRIT) plane. As can be seen in Table 1, most studies looking at non-cardinal color mechanisms have only looked in the isoluminant plane. A few have looked in the RG/LUM or TRIT/LUM planes, but fewer have looked across all three planes. The data so far seem to be supportive of non-cardinal mechanisms in the isoluminant plane, but less supportive in the other two planes. Of particular note, Krauskopf and coworkers [14,30] and Li and Lennie [25] did look in all three planes but only found evidence for non-cardinal mechanisms in the isoluminant plane (but cf. Flanagan et al. [35]). Webster and Mollon [17,18] and Gunther [6] found weak non-cardinal mechanisms outside of the isoluminant plane. However, other studies have found evidence for non-cardinal mechanisms in the RG/LUM [20,24,28] and TRIT/LUM [20] planes. Consequently, it is not yet clear how strong the non-cardinal mechanisms are outside of the isoluminant plane. This study thus tests two hypotheses: (1) there are individual differences in the presence of non-cardinal mechanisms, and (2) noncardinal mechanisms only exist (or are stronger) in the isoluminant (RG/TRIT) plane of color space.
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a ViewSonic G90fB monitor (19 in. display, 100 Hz refresh rate, 1024 × 768 pixel resolution). The monitor was calibrated by linearizing the voltage/luminance relationship independently for each of the three phosphors in the display, using the Gamma Correction System (CRS) and a ColorCAL (CRS). Because changes in calibration could produce luminance artifacts, calibration was verified daily by measuring the luminance of the red, green, violet, and chartreuse phases of the cardinal stimuli with a PR-655 spectroradiometer (Photo Research). Any day on which the red versus green (or the violet versus chartreuse) Michelson luminance contrast [e.g., LUMred − LUMgreen ∕LUMred LUMgreen ] was >2% the monitor was recalibrated. The subjects were seated with their heads situated in a chinrest to maintain a viewing distance of 57 cm. The experiment was performed in a dark, windowless room. Subjects responded on a CB6 response box (CRS). C. Isoluminance RG isoluminance varies considerably across subjects due to differences in photopigment optical density [42] and L:M cone ratio [42–44]. TRIT isoluminance varies across subjects largely due to variation in macular pigment, which selectively absorbs wavelengths below 500 nm [45,46], making the violet phase of the TRIT stimulus appear darker. Thus, if the same RG and TRIT stimuli are used for all subjects, many subjects would experience a luminance artifact in the stimuli. Further, spatiotemporal stimulus attributes stimulate neuronal receptive fields differently and alter isoluminance [47,48]. For these reasons, all of the stimuli in the isoluminance plane [RG, TRIT, orange/turquoise (OT), and purple/lime (PL)] were set to be isoluminant for each subject and each stimulus type.
A. Subjects In each plane of color space, one female subject, age 39, and five male subjects (four in the TRIT/LUM plane; Wabash College has an all-male student body), ages 18–22, participated. All subjects had normal color vision, as assessed by the Farnsworth–Munsell 100 Hue (FM100) test (error scores
Vol. 31, No. 4 / April 2014 / J. Opt. Soc. Am. A
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Non-cardinal color mechanism strength differs across color planes but not across subjects Karen L. Gunther Psychology Department, Wabash College, 301 West Wabash Avenue, Crawfordsville, Indiana 47933, USA ([email protected]) Received September 5, 2013; revised December 20, 2013; accepted January 13, 2014; posted January 14, 2014 (Doc. ID 196918); published February 25, 2014 This study tested two hypotheses: (1) that non-cardinal color mechanisms may be due to individual differences: some subjects have them (or have stronger ones), while other subjects do not; and (2) that non-cardinal mechanisms may be stronger in the isoluminant plane of color space than in the two planes with luminance. Five to six subjects per color plane were tested on three psychophysical paradigms: adaptation, noise masking, and plaid coherence. There were no consistent individual differences in non-cardinal mechanism strength across the three paradigms. In group-averaged data, non-cardinal mechanisms appear to be weaker in the two planes with luminance than in the isoluminant plane. © 2014 Optical Society of America OCIS codes: (330.0330) Vision, color, and visual optics; (330.1720) Color vision; (330.5510) Psychophysics; (330.7320) Vision adaptation. http://dx.doi.org/10.1364/JOSAA.31.00A293
1. INTRODUCTION We know that retinal ganglion cells and neurons in the lateral geniculate nucleus (LGN) of the thalamus respond best to variations in black versus white [i.e., luminance (LUM)], reddish versus greenish (RG), and violet versus chartreuse [loosely bluish versus yellowish, i.e., tritan (TRIT)] [1–4]. These color pairings are known as the cardinal axes of color space because they define the axes of a three-dimensional color space (see Fig. 1). Colors beyond these, such as orange and turquoise, form the non-cardinal (or higher order) axes. Neural mechanisms underlying the perception of noncardinal colors have not been found in the retina or the LGN (other than possibly the S– cells of Tailby et al. [5]); thus they must arise in the cortex. (Note: by “mechanism” I mean a group of neurons tuned to respond to certain colors—see Gunther [6] for a more complete discussion of mechanisms.) Neurophysiological evidence for cortical non-cardinal mechanisms has been found. For example, Lennie et al. [7] and Tailby et al. [8] electrophysically recorded from macaque neurons and found that primary visual cortex (V1) neuronal preferences were spread throughout color space. In LGN, in contrast, neuronal preferences were clustered around the cardinal colors [7]. Similarly, Kiper et al. [9] found a wide range of color preferences for neurons in V2. Using principal components analysis, pattern classification, and idealized modeling of color tuning on functional magnetic resonance imaging (fMRI) data from human subjects, Brouwer and Heeger [10] found that color tuning in the isoluminant plane, including non-cardinal colors, was most robust in cortical areas V4 and VO1; good in V1, V2, and V3; and poor in LO1, LO2, V3A/B, and MT. Parkes et al. [11] found that the V1 fMRI response more clearly separated prototypical (not cardinal) red, green, blue, and yellow than it separated the 1084-7529/14/04A293-10$15.00/0
cardinal (i.e., LGN) colors. Using both electrophysiology and fMRI in macaques, Conway et al. [12] found neurons in and around V4 that were tuned to a wide array of colors. Psychophysical measurements can show if these noncardinal-preferring neurons are used for color vision. A variety of psychophysical techniques have been used to search for neural mechanisms underlying the non-cardinal colors, including adaptation [13–19], factor analysis [20], masking [21–27], plaid coherence [28–30], and visual search [6,31,32]. As can be seen in Table 1, the results have been mixed: several studies have found evidence for non-cardinal mechanisms, others have not, and still others have found their existence in some but not all subjects or in some but not all planes of color space. Note that the variability in results is not correlated with paradigm—it is not the case that masking always finds non-cardinal mechanisms while adaptation does not, for example. In his comprehensive review of the psychophysical non-cardinal literature, Eskew [33] concluded that “no consensus on higher order mechanisms has been reached” (p. 2686). A couple of solutions to this conundrum have been proposed. First, Eskew [33] proposed from his literature review, and Hansen and Gegenfurtner [27] empirically determined, that studies that plot colors in cone contrast space (e.g., [23,26]) tend to not find non-cardinal mechanisms, while those that use Derrington–Krauskopf–Lennie (DKL) color opponency space (Fig. 1) tend to find support (most of the rest of the references in Table 1). Second, Stoughton et al. [19], in macaques, found that gratings, which tap cortical neurons, reveal non-cardinal mechanisms, but full-field stimuli, which better stimulate LGN neurons, do not. However, studies where some but not all subjects exhibit non-cardinal mechanisms [16–18,25,28,34] cannot be explained by stimulus parameters or which color space is used. © 2014 Optical Society of America
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K. L. Gunther
Fig. 1. DKL three-dimensional color space. Cone inputs are shown on axes: L, long-wavelength sensitive; M, medium-wavelength sensitive; S, short-wavelength sensitive. Reprinted from K. L. Gunther and K. R. Dobkins, “Independence of mechanisms tuned along cardinal and noncardinal axes of color space: evidence from factor analysis,” Vis. Res. 43, 683–696 (2003).[20]. Copyright 2003, with permission from Elsevier.
These inconsistent results, and the small sample sizes used, have led to the hypothesis that the existence of non-cardinal mechanisms may reflect individual differences [17,25,33,34,40]—some subjects may have them while others do not. The studies in Table 1 that support the existence of non-cardinal mechanisms may have obtained a lucky draw of all “non-cardinal subjects.” The studies that did not find evidence for non-cardinals may have drawn all subjects without non-cardinal mechanisms. The small sample sizes used in these studies would allow for skewed samples such as these. Some studies appear to have a mix of subject types [16–18,25,28,34]. Although the notion of individual differences has been suggested by others, and recently there has been increasing awareness that there is more variability across humans than had once been assumed, individual differences as an explanation for the discrepant noncardinal results has not yet been explored in depth across multiple paradigms.
Table 1. Review of the Literature on the Existence of Non-Cardinal Color Mechanismsa Reference Dobkins, Stoner, & Albright (1998) [28] Dobkins, Stoner, & Albright (1998) [28] D’Zmura (1991) [31] D’Zmura & Knoblauch (1998) [21] Eskew, Newton, & Giulianini (2001) [34] Flanagan, Cavanagh, & Favreau (1990) [35] Gegenfurtner & Kiper (1992) [22] Giesel, Hansen, & Gegenfurtner (2009) [36]
Giulianini & Eskew (1998) [23] Goda & Fujii (2001) [37] Gunther (2014) [6] Gunther & Dobkins (2003) [20] Hansen & Gegenfurtner (2006) [24] Hansen & Gegenfurtner (2013) [27] Kooi, DeValois, Switkes, & Grosof (1992) [29] Krauskopf & Gegenfurtner (1992) [13] Krauskopf, Williams, & Heeley (1982) [14] Krauskopf, Williams, Mandler, & Brown (1986) [15] Krauskopf, Williams, Mandler, & Brown (1986) [15] Krauskopf, Wu, and Farell (1996) [30] Li & Lennie (1997) [25] Mizokami, Paras, & Webster (2001) [16] Monnier & Nagy (2001) [32] Nagi, Neriani, & Young (2004) [38] Sankeralli & Mullen (1997) [26] Stoughton, Lafer-Sousa, Gagin, & Conway (2012) [19] Webster & Mollon (1991) [18] Webster & Mollon (1994) [17] Webster & Mollon (1994) [17] Zaidi & Halevy (1993) [39] a
Paradigm Plaid coherence unikinetic Plaid coherence bikinetic Visual search Masking Detection in noise Tilt aftereffect Noise masking Chromatic discrimination of variegated stimuli Masking Texture discrimination Visual search Factor analysis (n 41) Noise masking Noise masking Plaid coherence Adaptation Adaptation Adaptation Color discrimination and detection Plaid coherence Noise masking Adaptation Visual search Visual search Masking Adaptation Adaptation Adaptation, contrast detection Adaptation, reaction time Continuously changing colors
RG/TRIT Plane n
RG/LUM Plane n
TRIT/LUM Plane n
2/6,+ 4/6 weak 1/1 3/3 3/3 1/6 3/3 weak
3/3 weak 3/3
3/3 weak
4/4
0/3 4/4 10/10 + 3/3 No 5/5 10/10
10/10 + 3/3, all weak 10/10 + 3/3, all weak Yes Yes 4/4 Yes in 9 pooled subjects
1/1 weak 1 no, 1 weak 2/2 2/2 2/2 2/3 1 strong, 2 weak 3/3 5/5
0/2
Not shown
0/2 0/2
0/2 0/1
0/3 2/2 (monkeys) 2 strong, 2 weak 2/3
2/2 3/3 weak
Yes (n ?) 1 strong, 2 weak
2/2
1 weak
1 weak
2/2
Numbers represent the number of subjects demonstrating non-cardinal mechanisms out of the total number of subjects tested.
K. L. Gunther
This hypothesis of individual differences in the existence of non-cardinal mechanisms is tested here by searching for noncardinal mechanisms across three paradigms: adaptation, masking, and plaid coherence. I am unaware of any other studies that have used multiple paradigms to study the issue of individual differences in the existence of non-cardinal mechanisms. (Dobkins et al. [28] did measure both oculomotor responses and perceptual responses in the same subjects, but both to a plaid stimulus—multiple stimulus paradigms were not used. Likewise, Webster and Mollon [17] measured both contrast detection and reaction time in the same subjects, but both following adaptation. Neither study used multiple measures to explicitly examine individual differences.) By the multiple-paradigm method, if a given subject shows noncardinal mechanisms in one paradigm, he is predicted to do so in all three paradigms. If a different subject fails to show noncardinal mechanisms in one paradigm, he is predicted to not show them in any paradigm. A second aspect that was examined in this study is whether non-cardinal mechanisms exist in all three planes of color space or only in the isoluminant (RG/TRIT) plane. As can be seen in Table 1, most studies looking at non-cardinal color mechanisms have only looked in the isoluminant plane. A few have looked in the RG/LUM or TRIT/LUM planes, but fewer have looked across all three planes. The data so far seem to be supportive of non-cardinal mechanisms in the isoluminant plane, but less supportive in the other two planes. Of particular note, Krauskopf and coworkers [14,30] and Li and Lennie [25] did look in all three planes but only found evidence for non-cardinal mechanisms in the isoluminant plane (but cf. Flanagan et al. [35]). Webster and Mollon [17,18] and Gunther [6] found weak non-cardinal mechanisms outside of the isoluminant plane. However, other studies have found evidence for non-cardinal mechanisms in the RG/LUM [20,24,28] and TRIT/LUM [20] planes. Consequently, it is not yet clear how strong the non-cardinal mechanisms are outside of the isoluminant plane. This study thus tests two hypotheses: (1) there are individual differences in the presence of non-cardinal mechanisms, and (2) noncardinal mechanisms only exist (or are stronger) in the isoluminant (RG/TRIT) plane of color space.
Vol. 31, No. 4 / April 2014 / J. Opt. Soc. Am. A
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a ViewSonic G90fB monitor (19 in. display, 100 Hz refresh rate, 1024 × 768 pixel resolution). The monitor was calibrated by linearizing the voltage/luminance relationship independently for each of the three phosphors in the display, using the Gamma Correction System (CRS) and a ColorCAL (CRS). Because changes in calibration could produce luminance artifacts, calibration was verified daily by measuring the luminance of the red, green, violet, and chartreuse phases of the cardinal stimuli with a PR-655 spectroradiometer (Photo Research). Any day on which the red versus green (or the violet versus chartreuse) Michelson luminance contrast [e.g., LUMred − LUMgreen ∕LUMred LUMgreen ] was >2% the monitor was recalibrated. The subjects were seated with their heads situated in a chinrest to maintain a viewing distance of 57 cm. The experiment was performed in a dark, windowless room. Subjects responded on a CB6 response box (CRS). C. Isoluminance RG isoluminance varies considerably across subjects due to differences in photopigment optical density [42] and L:M cone ratio [42–44]. TRIT isoluminance varies across subjects largely due to variation in macular pigment, which selectively absorbs wavelengths below 500 nm [45,46], making the violet phase of the TRIT stimulus appear darker. Thus, if the same RG and TRIT stimuli are used for all subjects, many subjects would experience a luminance artifact in the stimuli. Further, spatiotemporal stimulus attributes stimulate neuronal receptive fields differently and alter isoluminance [47,48]. For these reasons, all of the stimuli in the isoluminance plane [RG, TRIT, orange/turquoise (OT), and purple/lime (PL)] were set to be isoluminant for each subject and each stimulus type.
A. Subjects In each plane of color space, one female subject, age 39, and five male subjects (four in the TRIT/LUM plane; Wabash College has an all-male student body), ages 18–22, participated. All subjects had normal color vision, as assessed by the Farnsworth–Munsell 100 Hue (FM100) test (error scores
