Abstract

We examine the functional role of S-cone signals on reaction time (RT) variability in human color vision. Stimuli were selected along red–green and blue–yellow cardinal directions and at random directions in the isoluminant plane of the color space. Trial-to-trial RT variability was not statistically independent but correlated across experimental conditions and exhibited 1/f noise spectra with an exponent close to unity in most of the cases. Regarding contrast coding, 1/f noise for random chromatic stimuli at isoluminance was similar to that for achromatic stimuli, thus suggesting that S-cone signals reduce variability of higher order color mechanisms. If we regard spatial coding, the effect of S-cone density in the retina on RT variability was investigated. The magnitude of 1/f noise at 16 min of arc (S-cone free zone) was higher than at 90 min of arc in the blue–yellow channel, and it was similar for the red–green channel. The results suggest that S-cone signals are beneficial and they modulate 1/f noise spectra at postreceptoral stages. The implications related to random multiplicative processes as a possible source of 1/f noise and the optimal information processing in color vision are discussed.

© 2012 Optical Society of America

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2011

J. M. Medina and J. A. Díaz, “Response variability of the red-green color vision system using reaction times,” Proc. SPIE 8001, 80013B (2011).
[CrossRef]

J. Correll, “Order from chaos? 1/f noise predicts performance on reaction time measures,” J. Exp. Soc. Psychol. 47, 830–835 (2011).
[CrossRef]

J. M. Medina, “Effects of multiplicative power law neural noise in visual information processing,” Neural Comput. 23, 1015–1046 (2011).
[CrossRef]

2010

C. T. Kello, G. D. A. Brown, R. Ferrer-i-Cancho, J. G. Holden, K. Linkenkaer-Hansen, T. Rhodes, and G. C. Van Orden, “Scaling laws in cognitive sciences,” Trends Cogn. Sci. 14, 223–232 (2010).
[CrossRef]

B. M. O’Donell, J. F. Barraza, and E. M. Colombo, “The effect of chromatic and luminance information on reaction times,” Vis. Neurosci. 27, 1–11 (2010).
[CrossRef]

B. Y. J. He, J. M. Zempel, A. Z. Snyder, and M. E. Raichle, “The temporal structures and functional significance of scale-free brain activity,” Neuron 66, 353–369 (2010).
[CrossRef]

2009

P. Allegrini, D. Menicucci, R. Bedini, L. Fronzoni, A. Gemignani, P. Grigolini, B. J. West, and P. Paradisi, “Spontaneous brain activity as a source of ideal 1/f noise,” Phys. Rev. E 80, 061914 (2009).
[CrossRef]

J. G. Holden, G. C. Van Orden, and M. T. Turvey, “Dispersion of response times reveals cognitive dynamics,” Psychol. Rev. 116, 318–342 (2009).
[CrossRef]

P. Grigolini, G. Aquino, M. Bologna, M. Lukovic, and B. J. West, “A theory of 1/f noise in human cognition,” Physica A 388, 4192–4204 (2009).
[CrossRef]

K. Torre and E.-J. Wagenmakers, “Theories and models for 1/fβ noise in human movement science,” Hum. Mov. Sci. 28, 297–318 (2009).
[CrossRef]

J. M. Medina, “1/fα noise in reaction times: a proposed model based on Pieron’s law and information processing,” Phys. Rev. E 79, 011902 (2009).
[CrossRef]

J. J. Nassi and E. M. Callaway, “Parallel processing strategies of the primate visual system,” Nat. Rev. Neurosci. 10, 360–372 (2009).
[CrossRef]

2008

A. A. Faisal, L. P. J. Selen, and D. M. Wolpert, “Noise in the nervous system,” Nat. Rev. Neurosci. 9, 292–303 (2008).
[CrossRef]

B. J. West, E. L. Geneston, and P. Grigolini, “Maximizing information exchange between complex networks,” Phys. Rep. 468, 1–99 (2008).
[CrossRef]

2007

M. D. Fox, A. Z. Snyder, J. L. Vincent, and M. E. Raichle, “Intrinsic fluctuations within cortical systems account for intertrial variability in human behavior,” Neuron 56, 171–184 (2007).
[CrossRef]

E. J. Wagenmakers and S. Brown, “On the linear relation between the mean and the standard deviation of a response time distribution,” Psychol. Rev. 114, 830–841 (2007).
[CrossRef]

C. T. Kello, B. C. Beltz, J. G. Holden, and G. C. Van Orden, “The emergent coordination of cognitive function,” J. Exp. Psychol. Gen. 136, 551–568 (2007).
[CrossRef]

J. D. Victor, E. M. Blessing, J. D. Forte, P. Buzas, and P. R. Martin, “Response variability of marmoset parvocellular neurons,” J. Physiol. 579, 29–51 (2007).
[CrossRef]

S. G. Solomon and P. Lennie, “The machinery of colour vision,” Nat. Rev. Neurosci. 8, 276–286 (2007).
[CrossRef]

2006

2005

V. A. Billock and B. H. Tsou, “Sensory recoding via neural synchronization: integrating hue and luminance into chromatic brightness and saturation,” J. Opt. Soc. Am. A 22, 2289–2298 (2005).
[CrossRef]

R. B. Stein, E. R. Gossen, and K. E. Jones, “Neuronal variability: noise or part of the signal?” Nat. Rev. Neurosci. 6, 389–397 (2005).
[CrossRef]

Y. G. Yu, R. Romero, and T. S. Lee, “Preference of sensory neural coding for 1/f signals,” Phys. Rev. Lett. 94, 108103 (2005).
[CrossRef]

T. L. Thornton and D. L. Gilden, “Provenance of correlations in psychological data,” Psychon. Bull. Rev. 12, 409–441 (2005).
[CrossRef]

D. Mitov and T. Totev, “How many pathways determine the speed of grating detection?” Vis. Res. 45, 821–825 (2005).
[CrossRef]

2004

N. R. A. Parry, S. Plainis, I. J. Murray, and D. J. McKeefry, “Effect of foveal tritanopia on reaction times to chromatic stimuli,” Vis. Neurosci. 21, 237–242 (2004).
[CrossRef]

2003

J. Miller and R. Ulrich, “Simple reaction time and statistical facilitation: a parallel grains model,” Cogn. Psychol. 46, 101–151 (2003).
[CrossRef]

K. Donner and P. Fagerholm, “Visual reaction time: neural conditions for the equivalence of stimulus area and contrast,” Vis. Res. 43, 2937–2940 (2003).
[CrossRef]

D. J. McKeefry, N. R. A. Parry, and I. J. Murray, “Simple reaction times in color space: the influence of chromaticity, contrast, and cone opponency,” Investig. Ophthalmol. Vis. Sci. 44, 2267–2276 (2003).
[CrossRef]

K. R. Gegenfurtner and D. C. Kiper, “Color vision,” Annu. Rev. Neurosci. 26, 181–206 (2003).
[CrossRef]

2002

A. Vassilev, M. Mihaylova, and C. Bonnet, “On the delay in processing high spatial frequency visual information: reaction time and VEP latency study of the effect of local intensity of stimulation,” Vis. Res. 42, 851–864 (2002).
[CrossRef]

J. R. Jiménez, J. M. Medina, L. del Jiménez Barco, and J. A. Díaz, “Binocular summation of chromatic changes as measured by visual reaction time,” Atten. Percept. Psychophys. 64, 140–147 (2002).
[CrossRef]

2001

J. A. Díaz, L. del Jiménez Barco, J. R. Jiménez, and F. Perez-Ocón, “Chromatic spatial summation at equiluminance,” Opt. Rev. 8, 388–396 (2001).
[CrossRef]

J. A. Díaz, L. del Jiménez Barco, J. R. Jiménez, and E. Hita, “Simple reaction time to chromatic changes along L&M-constant and S-constant cone axes,” Color Res. Appl. 26, 223–233 (2001).
[CrossRef]

T. Gisiger, “Scale invariance in biology: coincidence or footprint of a universal mechanism?” Biol. Rev. 76, 161–209 (2001).
[CrossRef]

D. L. Gilden, “Cognitive emissions of 1/f noise,” Psychol. Rev. 108, 33–56 (2001).
[CrossRef]

D. J. Calkins, “Seeing with S cones,” Prog. Retin. Eye Res. 20, 255–287 (2001).
[CrossRef]

2000

S. H. C. Hendry and R. C. Reid, “The koniocellular pathway in primate vision,” Annu. Rev. Neurosci. 23, 127–153 (2000).
[CrossRef]

D. M. Dacey, “Parallel pathways for spectral coding in primate retina,” Annu. Rev. Neurosci. 23, 743–775 (2000).
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Figures (11)

Fig. 1.
Fig. 1.

(a) Random chromatic stimuli at isoluminance (black circles) represented in the CIE 1931 chromaticity diagram. The empty circle indicates the reference adapting stimuli. The triangle indicates the monitor color gamut delimited by the coordinates of the red, green, and blue phosphor primaries (black diamonds). For the fixed reference stimuli, the schematic diagram at the top-right border indicates the corresponding L–M- and S-cone axis variations. Level of reference luminance: 15cd/m2. (b) Temporal and spatial configuration of the stimuli selected.

Fig. 2.
Fig. 2.

Plot of RT series (in ms) for random chromatic variations at isoluminance (right column) and those for achromatic variations (left column). Data are presented to observers JA, JM, and JR separately.

Fig. 3.
Fig. 3.

Plot of the SD (in ms) as a function of the mean RT (in ms) in logarithmic axes. Open and black circles indicate random chromatic variations at isoluminance and achromatic variations, respectively. Data correspond to observers JA, JM, and JR, separately.

Fig. 4.
Fig. 4.

Full logarithmic plot of the power spectrum generated from the RT series for random chromatic variations at isoluminance (open circles) and that for achromatic variations (black circles). Gray and black solid straight lines correspond to those fits taking chromatic and achromatic data, respectively. Gray and black numbers are their resulting slope, respectively. Numbers in parentheses are their associated standard errors. Data correspond to observers JA, JM, and JR, separately.

Fig. 5.
Fig. 5.

Plot of red–green and blue–yellow stimuli at isoluminance (black circles) in the CIE 1931 chromaticity diagram. The empty circle indicates the reference adapting stimulus. The triangle indicates the monitor color gamut delimited by the coordinates of the red, green, and blue phosphor primaries (black diamonds). For the fixed reference stimuli, the schematic diagram at the top-right border indicates the corresponding L–M and S-cone axis variations. Level of reference luminance: 12cd/m2. (b) Spatial configuration of the stimuli selected at 16 and 90 min of arc.

Fig. 6.
Fig. 6.

Plot of the RT series (in ms) series for red–green variations at isoluminance (L–M cone axis) at 16 and 90 min of arc. Data correspond to observers JA, JM, and JR, separately.

Fig. 7.
Fig. 7.

Plot of the RT series (in ms) series for blue–yellow variations at isoluminance (S-cone axis) at 16 and 90 min of arc. Data are presented for observers JA and MC, separately.

Fig. 8.
Fig. 8.

Plot of the SD (in ms) as a function of the mean RT (in ms) for blue–yellow variations (S-cone axis, right column) and red–green variations at isoluminance (L–M cone axis, left column) in logarithmic axes. Open and black circles indicate those stimuli selected at 16 and 90 min of arc. Data correspond to observers JA and MC, separately.

Fig. 9.
Fig. 9.

Full logarithmic plot of the power spectrum generated from RT series for blue–yellow variations (S-cone axis, right column) and red–green variations at isoluminance (L–M cone axis, left column). Black and gray solid straight lines indicate those fits at 16 and 90 min of arc, respectively. Black and gray and numbers are their obtained slope, respectively. Numbers in parentheses are their associated standard errors. Data correspond to observers JA and MC, separately.

Fig. 10.
Fig. 10.

Linear plot of the hazard functions (in events per ms) as a function of the cone contrast for red–green variations at isoluminance (L–M cone axis). Black and gray lines correspond to a stimulus size of 16 and 90 min of arc, respectively. Data for observer JA and MC are shown separately.

Fig. 11.
Fig. 11.

Linear plot of the hazard functions (in events per ms) as a function of the cone contrast for blue–yellow variations at isoluminance (S-cone axis). Black and gray lines indicate a stimulus size of 16 and 90 min of arc, respectively. Data for observer JA and MC are shown separately.

Equations (3)

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tRT=tRT0+μSp,
tRT=tRT0[1+(S0/S)p].
RTobservationsPiéron’s law+threshold fluctuations.

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