Abstract
Although color term ‘Gold’ is commonly used, traditional color science cannot deal with ‘Gold’ because there is no region corresponding to ‘Gold’ in the chromaticity diagram generated based on the color matching experiments. Appearance of an object changes from ‘Yellow’ to ‘Gold’ with an increase in the specular reflectance, and understanding how we discriminate ‘Gold’ from ‘Yellow’ is tightly related to an important problem of how we perceive surface reflectance or gloss of objects. To understand neural processes underlying gloss perception, we conducted a series of experiments. When we compared neural activities evoked by objects with specular and matte surfaces using functional magnetic resonance imaging in monkeys, stronger activities to specular surface were observed in areas along the ventral pathway of the visual cortex including the inferior temporal (IT) cortex that plays an essential role in object discrimination. We also recorded single neuron activities from the IT cortex and found that there exist neurons that are selectively responding to specific gloss, and that as a population, these neurons systematically represented a variety of glosses. We speculate that visual features distinguishing surface glosses are detected in early visual areas and this information is integrated along the ventral visual pathway to form neural representation of a variety of glosses of object images in the IT cortex. Neural mechanisms underlying discrimination between ‘Gold’ and ‘Yellow’ should at least in part lie in this process.
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Kelly, K.L.: Color designations for lights. J. Opt. Soc. Am. A 33, 627–632 (1943)
Boynton, R.M., Olson, C.X.: Locating basic colors in the OSA space. Color Research & Application 12, 94–105 (1987)
Uchikawa, K., Boynton, R.M.: Categorical color perception of Japanese observers: comparison with that of Americans. Vision Res. 27, 1825–1833 (1987)
Komatsu, H.: Mechanisms of central color vision. Curr. Opin. Neurobiol. 8, 503–508 (1998)
Gegenfurtner, K.R.: Cortical mechanisms of colour vision. Nat. Rev. Neurosci. 4, 563–572 (2003)
Solomon, S.G., Lennie, P.: The machinery of colour vision. Nat. Rev. Neurosci. 8, 276–286 (2007)
Zeki, S.: Colour coding in the cerebral cortex: the reaction of cells in monkey visual cortex to wavelengths and colours. Neuroscience 9, 741–765 (1983)
Wachtler, T., Sejnowski, T.J., Albright, T.D.: Representation of color stimuli in awake macaque primary visual cortex. Neuron 37, 681–691 (2003)
Kusunoki, M., Moutoussis, K., Zeki, S.: Effect of background colors on the tuning of color-selective cells in monkey area V4. J. Neurophysiol 95, 3047–3059 (2006)
Hanazawa, A., Komatsu, H., Murakami, I.: Neural selectivity for hue and saturation of colour in the primary visual cortex of the monkey. Eur. J. Neurosci. 12, 1753–1763 (2000)
Lennie, P., Krauskopf, J., Sclar, G.: Chromatic mechanisms in striate cortex of macaque. J. Neurosci. 10, 649–669 (1990)
Conway, B.R., Moeller, S., Tsao, D.Y.: Specialized color modules in macaque extrastriate cortex. Neuron 56, 560–573 (2007)
Kiper, D.C., Fenstemaker, S.B., Gegenfurtner, K.R.: Chromatic properties of neurons in macaque area V2. Vis. Neurosci. 14, 1061–1072 (1997)
Komatsu, H., Ideura, Y., Kaji, S., Yamane, S.: Color selectivity of neurons in the inferior temporal cortex of the awake macaque monkey. J. Neurosci. 12, 408–424 (1992)
Xiao, Y., Wang, Y., Felleman, D.J.: A spatially organized representation of colour in macaque cortical area V2. Nature 421, 535–539 (2003)
Zeki, S.: The representation of colours in the cerebral cortex. Nature 284, 412–418 (1980)
Koida, K., Komatsu, H.: Effects of task demands on the responses of color-selective neurons in the inferior temporal cortex. Nat. Neurosci. 10, 108–116 (2007)
Matsumora, T., Koida, K., Komatsu, H.: Relationship between color discrimination and neural responses in the inferior temporal cortex of the monkey. J. Neurophysiol. 100, 3361–3374 (2008)
Okazawa, G., Koida, K., Komatsu, H.: Categorical properties of the color term “GOLD”. J. Vis. 11(8):4, 1–19 (2011)
Ferwerda, J.A., Pellacini, F., Greenberg, D.P.: A psychophysically-based model of surface gloss perception. In: Proceedings of SPIE Human Vision and Electronic Imaging, vol. 4299, pp. 291–301 (2001)
Fleming, R.W., Dror, R.O., Adelson, E.H.: Real-world illumination and the perception of surface reflectance properties. J. Vis. 3, 347–368 (2003)
Kim, J., Marlow, P., Anderson, B.L.: The perception of gloss depends on highlight congruence with surface shading. J. Vis. 11(9):4, 1–19 (2011)
Motoyoshi, I., Nishida, S., Sharan, L., Adelson, E.H.: Image statistics and the perception of surface qualities. Nature 447, 206–209 (2007)
Nishida, S., Shinya, M.: Use of image-based information in judgments of surface-reflectance properties. J. Opt. Soc. Am. A 15, 2951–2965 (1998)
Beck, J., Prazdny, S.: Highlights and the perception of glossiness. Percept Psychophys 30, 407–410 (1981)
Nishio, A., Goda, N., Komatsu, H.: Neural selectivity and representation of gloss in the monkey inferior temporal cortex. J. Neurosci. 32, 10780–10793 (2012)
Yasuda, M., Banno, T., Komatsu, H.: Color selectivity of neurons in the posterior inferior temporal cortex of the macaque monkey. Cereb. Cortex 20, 1630–1646 (2009)
Okazawa, G., Goda, N., Komatsu, H.: Selective responses to specular surfaces in the macaque visual cortex revealed by fMRI. NeuroImage 63, 1321–1333 (2012)
Okazawa, G., Komatsu, H.: Image statistics for golden appearance of a painting by a Japanese Edo-era artist Jakuchu Ito. In: CCIW 2013 Fourth Computational Color Imaging Workshop, Chiba, Japan (March 2013)
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Komatsu, H., Nishio, A., Okazawa, G., Goda, N. (2013). ‘Yellow’ or ‘Gold’?: Neural Processing of Gloss Information. In: Tominaga, S., Schettini, R., Trémeau, A. (eds) Computational Color Imaging. CCIW 2013. Lecture Notes in Computer Science, vol 7786. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36700-7_1
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DOI: https://doi.org/10.1007/978-3-642-36700-7_1
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