Vattuone, Nicolás R. (2021) Determinación teórico-experimental de la geometría del espacio de colores percibidos bajo la influencia de un entorno cromático / Experimental and theoretical determination of the geometry of the space of colors perceived on a chromatic surround. Tesis Doctoral en Física, Universidad Nacional de Cuyo, Instituto Balseiro.
![[img]](/style/images/fileicons/application_pdf.png)
| PDF (Tesis) Español 17Mb |
Resumen en español
La experiencia perceptual suscitada por un estímulo no está determinada unívocamente por las propiedades físicas del estímulo, sino también por el contexto en que es percibido. En particular, el color con que un objeto es percibido depende de la cromaticidad del entorno del objeto, fenómeno conocido como inducción cromática. Esta dependencia implica que la composición espectral de un estímulo visual es insuficiente para especificar el color percibido. En esta tesis construimos un modelo para el espacio de colores que incluye en su descripción la inducción cromática, permitiendo generalizar las nociones de “color” y “distancia entre colores” a paradigmas experimentales en los que la cromaticidad del entorno es variable. Construimos la geometría del espacio de colores mediante la medición de los umbrales de discriminación, es decir, la cantidad mínima en que se debe modificar un estímulo para que un sujeto perciba una diferencia. Una hipótesis fundamental de nuestro modelo es que la inducción cromática adopta la forma más sencilla posible en esta geometría, es decir, que es isotrópica y homogénea. Para poner a prueba esta hipótesis hicimos una serie de experimentos de discriminación cromática y experimentos de matcheo asimétrico entre estímulos presentados en distintos entornos. Los experimentos mostraron evidencia de dichas simetrías, lo cual permite describir los resultados experimentales mediante una ley universal, es decir, que no depende de específicamente qué colores se comparan sino solo de su distancia perceptual. Luego, analizamos resultados experimentales previos de discriminación cromática y de matcheo asimétrico, mostrando que el modelo describe muy bien los experimentos con una cantidad mínima de parámetros ajustados. Por ultimo, estudiamos también el efecto del lenguaje y la memoria en la percepción cromática. En primer lugar, utilizamos nuestro modelo para describir un experimento previo que sostenía que los umbrales de discriminación estaban determinados por categorías lingüísticas. En el marco de nuestra teoría, los resultados descriptos en ese trabajo pueden explicarse por efectos enteramente perceptuales, por lo cual, no aportan evidencia sobre el rol del lenguaje en la discriminación cromática. En segundo lugar, realizamos experimentos que muestran que la memoria cromática está estructurada en términos de colores focales y colores frontera (atractores y repulsores, respectivamente), y describimos la variabilidad poblacional de esta estructura.
Resumen en inglés
The perceptual experience elicited by a stimulus is not uniquely determined by its physical properties, but also by the context in which it is perceived. In particular, the color with which an object is perceived depends on the chromaticity of the surround, a phenomenon known as chromatic induction. This influence implies that the spectral composition of a visual stimulus is insufficient to specify the perceived color. In this thesis we built a model for color space that includes chromatic induction, with which the notions of “color” and “distance between colors” can be generalized to experimental paradigms in which the chromaticity of the environment is variable. The geometry of color space was constructed by measuring discrimination thresholds, that is, the minimum amount by which a stimulus must be modified for a subject to perceive a difference. A fundamental hypothesis of our model is that chromatic induction takes the simplest possible form in this geometry, that is, that it is isotropic and homogeneous. To test this hypothesis, we conducted a series of color discrimination experiments and asymmetric matching experiments between stimuli surrounded by varying chromaticities. The experiments showed evidence of these symmetries, implying that the experimental results may be described by a universal law, that is, one which does not depend on specifically which colors are compared but only on their perceptual distance. Then, we analyzed previous experimental results of chromatic discrimination and asymmetric matching, showing that the model provides an accurate description of the experiments with a minimal number of adjusted parameters. Finally, we also studied the effect of language and memory on color perception. First, we employed our model to describe a previous experiment that claimed that discrimination thresholds were determined by linguistic categories. Within the framework of our theory, their results could by entirely explained by perceptual effects, impliying that they did not convey evidence on the role of language in color discrimination. Second, we conducted experiments that show that color memory is structured in terms of focal colors and boundary colors (attractors and repulsors, respectively), and we described the population variability of this structure.
| Tipo de objeto: | Tesis (Tesis Doctoral en Física) |
|---|---|
| Palabras Clave: | Color; Geometry; Geometría; [Perception; Precepción; Chromatic induction; Inducción cromática; Psychophysics; Psicofísica; Neuroscience; Neurociencia] |
| Referencias: | [1] Brouwer, G. J., Heeger, D. J. Decoding and reconstructing color from responses in human visual cortex. Journal of Neuroscience, 29 (44), 13992–14003, nov. 2009. URL https://doi.org/10.1523/jneurosci.3577-09.2009. viii, 16, 17 [2] Bowmaker, J. K., Dartnall, H. J. Visual pigments of rods and cones in a human retina. The Journal of Physiology, 298 (1), 501–511, ene. 1980. URL https://doi. org/10.1113/jphysiol.1980.sp013097. ix, 29 [3] Crawford, B. H. The scotopic visibility function. Proceedings of the Physical Society. Section B, 62 (5), 321–334, may 1949. URL https://doi.org/10.1088/ 0370-1301/62/5/305. ix, 34 [4] Judd. Report on colorimetry and artificial daylight. J. Opt. Soc. Am., 38 (9), 803–803, Sep 1948. URL http://www.osapublishing.org/abstract.cfm?URI= josa-38-9-803. ix, 34 [5] Sharpe, L. T., Stockman, A., Jagla,W., J¨agle, H. A luminous efficiency function v() for daylight adaptation. Journal of Vision, 5 (1), 948–968, 2005. 171 [6] Guild, J. The colorimetric properties of the spectrum. Philosophical Transactions of the Royal Society of London A, 230 (681–693), 6149–187, 1932. ix, 34, 70 [7] Hansen, T., Gegenfurtner, K. R. Classification images for chromatic signal detection. Journal of the Optical Society of America A, 22 (10), 2081, oct. 2005. URL https://doi.org/10.1364/josaa.22.002081. ix, 36 [8] Resnikoff, H. L. Differential geometry and color perception. Journal of Mathematical Biology, 1, 97–131, 1974. x, 18, 19, 37, 41, 43, 47, 64, 76, 86 [9] Provenzi, E. Geometry of color perception. part 1: structures and metrics of a homogeneouscolor space. Journal of Mathematical Neuroscience, 10 (7), 2020. x, 19, 21, 37, 43, 64, 86 [10] Krauskopf, J., Gegenfurtner, K. Color discrimination and adaptation. Vision Research, 32 (11), 2165–2175, 1992. xiv, 47, 60, 61, 65, 73, 74, 76, 86, 91, 94, 100, 125, 150, 152, 182 [11] Danilova, M. V., Mollon, J. Parafoveal color discrimination: a chromaticity locus of enhanced discrimination. Journal of vision, 10 (1), 4–4, 2010. xv, xv, 103, 105, 107, 108 [12] Danilova, M., Mollon, J. Foveal color perception: minimal thresholds at a boundary between perceptual categories. Vision research, 62, 162–172, 2012. xv, 103, 105, 118 [13] Klauke, S., Wachtler, T. “tilt” in color space: Hue changes induced by chromatic surrounds. Journal of Vision, 15 (13), 1–11, 2015. xvi, 37, 53, 65, 88, 121, 122, 150 [14] Borges, J. L. El hacedor. Argentina, Buenos Aires: Emece Editores SA, 1960. 3 [15] Beaver, H. A. Ophthalmology, 3rd edition. Journal of Neuro-Ophthalmology, 29 (4), 371, dic. 2009. URL https://doi.org/10.1097/01.wno.0000365408. 81897.14. 3 [16] Fish, W. Philosophy of Perception. Routledge, 2010. URL https://doi.org/10.4324/9780203880586. 8 [17] Robinson, H. Perception. London: Routledge, 1994. [18] (Ed), E. Z. Stanford Encyclopedia of Philosophy – http://plato.stanford.edu/. The Metaphysics Research Lab Center for the Study of Language and Information Stanford University Stanford, CA 94305-4115, 2015. URL http://plato.stanford.edu/. 8 [19] No¨e, A. Action in perception. Cambridge, Mass: MIT Press, 2005. 10 [20] Moser, E. I., Kropff, E., Moser, M.-B. Place cells, grid cells, and the brain’s spatial representation system. Annual Review of Neuroscience, 31 (1), 69–89, 2008. URL https://doi.org/10.1146/annurev.neuro.31.061307. 090723, pMID: 18284371. 10 [21] Vilarroya, O. Neural representation. a survey-based analysis of the notion. Frontiers in Psychology, 8, ago. 2017. URL https://doi.org/10.3389/fpsyg.2017. 01458. 11 [22] Bruce, V. Visual perception : physiology, psychology, and ecology. Hove New York: Psychology Press, 2003. 13 [23] Weber, E. H. De pulsu, resorptione, auditu et tactu (on stimulation, response, hearing and touch). Annotationes, anatomical et physiological. Leipzig, Austria: Koehler, 1834. 14 [24] Read, J. The place of human psychophysics in modern neuroscience. Neuroscience, 296, 116–129, jun. 2015. URL https://doi.org/10.1016/j. neuroscience.2014.05.036. 15 [25] Kim, I., Hong, S.W., Shevell, S. K., Shim,W. M. Neural representations of perceptual color experience in the human ventral visual pathway. Proceedings of the National Academy of Sciences, 117 (23), 13145–13150, mayo 2020. URL https://doi.org/10.1073/pnas.1911041117. 15 [26] Bouvier, S. E., Engel, S. A. Behavioral deficits and cortical damage loci in cerebral achromatopsia. Cerebral Cortex, 16 (2), 183–191, abr. 2005. URL https://doi.org/10.1093/cercor/bhi096. 16 [27] Mongillo, G., Loewenstein, Y. Neuroscience: Formation of a percept in the rat cortex. Current Biology, 27 (11), R423–R425, jun. 2017. URL https://doi.org/10.1016/j.cub.2017.04.019. 17 [28] Linster, C., Johnson, B. A., Yue, E., Morse, A., Xu, Z., Hingco, E. E., et al. Perceptual correlates of neural representations evoked by odorant enantiomers. The Journal of Neuroscience, 21 (24), 9837–9843, dic. 2001. URL https://doi.org/10.1523/jneurosci.21-24-09837.2001. 17 [29] Aronov, D., Nevers, R., Tank, D. W. Mapping of a non-spatial dimension by the hippocampal–entorhinal circuit. Nature, 543 (7647), 719–722, 2017. 18 [30] Radvanski, B. A., Dombeck, D. A. An olfactory virtual reality system for mice. Nature Communications, 9 (1), 839, 2018. 18 [31] Constantinescu, A. O., O’Reilly, J. X., Behrens, T. E. J. Organizing conceptual knowledge in humans with a gridlike code. Science, 352 (6292), 1464–1468, 2016. 18, 20 [32] Kumaran, D., Banino, A., Blundell, C., Hassabis, D., Dayan, P. Computations underlying social hierarchy learning: Distinct neural mechanisms for updating and representing self-relevant information. Neuron, 92 (5), 1135–1147, 2016. 18 [33] Bellmund, J. L. S., G¨ardenfors, P., Moser, E. I., Doeller, C. F. Navigating cognition: Spatial codes for human thinking. Science, 362 (6415), eaat6766, 2018. 18 [34] Horner, A. H., Bisby, J. A., Zotow, E., Bush, D., Burgess, N. Grid-like processing of imagined navigation. Current Biology, 26 (6), 842–847, 2018. 18 [35] Bellmund, J. L. S., Deuker, L., Schr¨oder, T. N., Doeller, C. F. Grid-cell representations in mental simulation. Elife, 5, e17089, 2016. 18 [36] Kaplan, R., Schuck, N.W., Doeller, C. F. The role of mental maps in decision-making. Trends in Neurosciences, 40 (5), 256–259, 2017. 18 [37] von Helmholtz, H. Physiological optics der Akademie zu Berlin. 17. Dezember 1891. Vision Research, 29:11, 163–1647, 1896. 19, 37 [38] Schr¨odinger, E. Grundlinien einer theorie der farbenmetrik im tagessehen. Annalen der Physik, 368 (21), 427–456, 1920. 37, 47 [39] Stiles, W. S. A modified helmholtz line element in brightness-colour space. Proceedings of the Physical Society, 58 (1), 41–65, 1946. 19, 47 [40] Berthier, M., Provenzi, E. When geometry meets psycho-physics and quantum mechanics: Modern perspectives on the space of perceived colors. En: Lecture Notes in Computer Science, p´ags. 621–630. Springer International Publishing, 2019. URL https://doi.org/10.1007/978-3-030-26980-7_64. 19, 86 [41] Berthier, M. Geometry of color perception. part 2: perceived colors from real quantum states and hering’s rebit. The Journal of Mathematical Neuroscience, 10 (1), sep. 2020. URL https://doi.org/10.1186/s13408-020-00092-x. 19, 86 [42] Rieke, F., Baylor, D. A. Single-photon detection by rod cells of the retina. Reviews of Modern Physics, 70 (3), 1027–1036, jul. 1998. URL https://doi.org/10.1103/revmodphys.70.1027. 22 [43] Schanda, J. Colorimetry: understanding the CIE system. Choice Reviews Online, 45 (06), 45–3204–45–3204, feb. 2008. URL https://doi.org/10.5860/ choice.45-3204. 25 [44] Dubois, E. The structure and properties of color spaces and the representation of color images. Synthesis Lectures on Image, Video, and Multimedia Processing, 4 (1), 1–129, ene. 2009. URL https://doi.org/10.2200/s00224ed1v01y200910ivm011. 25 [45] Baylor, D. A., Nunn, B. J., Schnapf, J. L. The photocurrent, noise and spectral sensitivity of rods of the monkey macaca fascicularis. The Journal of Physiology, 357 (1), 575–607, dic. 1984. URL https://doi.org/10.1113/jphysiol.1984. sp015518. 29 [46] Baylor, D. How photons start vision. Proceedings of the National Academy of Sciences, 93 (2), 560–565, ene. 1996. URL https://doi.org/10.1073/pnas. 93.2.560. 30 [47] Zhaoping, L., Geisler, W. S., May, K. A. Human wavelength discrimination of monochromatic light explained by optimal wavelength decoding of light of unknown intensity. PLoS ONE, 6 (5), e19248, 2011. 30 [48] da Fonseca, M., Samengo, I. Derivation of human chromatic discrimination ability from an information-theoretical notion of distance in color space. Neural Computation, 28 (12), 2628–2655, 2016. 30, 37, 47, 86, 149 [49] Song, Z., Zhou, Y., Juusola, M. Random photon absorption model elucidates how early gain control in fly photoreceptors arises from quantal sampling. Frontiers in Computational Neuroscience, 10, jun. 2016. URL https://doi.org/10.3389/fncom.2016.00061. 30 [50] Stockman, A., Sharpe, L. T. Spectral sensitivities of the middle- and long-wavelength sensitive cones derived from measurements in observers of known genotype. Vision Research, 40 (13), 1711–1737, 2000. 32, 66, 122 [51] Teufel, H. J.,Wehrhahn, C. Evidence for the contribution of s cones to the detection of flicker brightness and red–green. Journal of the Optical Society of America A, 17 (6), 994, jun. 2000. URL https://doi.org/10.1364/josaa.17.000994. 34, 123, 135, 152 [52] Masland, R. H. The neuronal organization of the retina. Neuron, 76 (2), 266–280, oct. 2012. URL https://doi.org/10.1016/j.neuron.2012.10.002. 35 [53] Derrington, A. M., Krauskopf, J., Lennie, P. Chromatic mechanisms in lateral geniculate nucleus of macaque. Journal of Physiology, 357 (1), 241–265, 1984. 36, 37, 72 [54] Johnston, J., Esposti, F., Lagnado, L. Color vision: Retinal blues. Current Biology, 22 (16), R637–R639, ago. 2012. URL https://doi.org/10.1016/j.cub. 2012.07.022. 36 [55] MacAdam, D. L. On the geometry of color space. Journal of the Franklin Institute, 238 (5), 195–201, 1944. 37, 47 [56] Chichilnisky, E. J., Wandell, B. A. Seeing gray through the ON and OFF pathways. Visual Neuroscience, 13 (3), 591–596, mayo 1996. URL https://doi.org/10. 1017/s0952523800008270. 46, 69 [57] von Helmholtz, H. K¨urzeste linien im farbensystem: Auszug aus einer abhandlung gleichen titels in sitzgsber. der akademie zu berlin. 17. dezember 1891. Zeitschrift f¨ur Psychologie und Physiologie der Sinnesorgane, 3, 108–122, 1892. 47 [58] Silberstein, L. Investigations on the intrinsic properties of the color domain. Journal of the Optical Society of America, 33 (1), 1–10, 1943. 47 [59] da Fonseca, M., Samengo, I. Novel perceptually uniform chromatic space. Neural Computation, 30 (6), 1612–1623, 2018. URL https://doi.org/10.1162/ neco_a_01073, pMID: 29566354. 47, 86, 149, 152 [60] Jameson, D., Hurvich, L. M. Opponent chromatic induction: Experimental evaluation and theoretical account. JOSA, 51 (1), 46–53, 1961. 53 [61] Jameson, D., Hurvich, L. M. Theory of brightness and color contrast in human vision. Vision Research, 4 (1-2), 135–154, mayo 1964. URL https://doi.org/10.1016/0042-6989(64)90037-9. [62] Shevell, S. K. The dual role of chromatic backgrounds in color perception. Vision Research, 18 (12), 1649–1661, 1978. URL https://www.sciencedirect. com/science/article/pii/0042698978902572. 53, 65 [63] Atick, J. J. Could information theory provide an ecological theory of sensory perception? network: Computation in neural systems. Network: Computation in neural systems, 3 (2), 213–251, 1992. 56 [64] Lee, J. M. Introduction to Riemannian Manifolds. Springer International Publishing, 2018. URL https://doi.org/10.1007/978-3-319-91755-9. 61 [65] MacAdam, D. L. Visual sensitivities to color differences in daylight. Journal of the Optical Society of America, 32 (5), 247–274, 1942. 65, 147, 182 [66] Danilova, M., Mollon, J. Is discrimination enhanced at the boundaries of perceptual categories? a negative case. Proceedings of the Royal Society B: Biological Sciences, 281 (1785), 20140367, 2014. 65, 103, 105, 118 [67] Kellner, C. J., Wachtler, T. Stimulus size dependence of hue changesinduced by chromatic surrounds. Journal of the Optical Society of America, 33 (3), A267–A272, 2016. 65, 66 [68] Rinner, O., Gegenfurtner, K. R. Time course of chromatic adaptation for color appearance and discrimination. Vision Research, 40 (14), 1813–1826, jun. 2000. URL https://doi.org/10.1016/s0042-6989(00)00050-x. 67 [69] Commission Internationale de l’Eclairage. Proceedings 1931. Cambridge: Cambridge University Press, 1932. 70 [70] Stiles, W. S., Burch, J. M. Npl colour-matching investigation: final report. Journal of Modern Optics, 6 (1), 1–26, 1959. 86 [71] Wyszecki, G., Stiles, W. S. Color Science: Concepts and Methods, Quantitative Data and Formulae. New York: Wiley Interscience, 2000. 70, 79 [72] Wachtler, T., Albright, T. D., Sejnowski, T. J. Nonlocal interactions in color perception: nonlinear processing of chromatic signals from remote inducers. Vision Research, 12, 1535–1546, jun. 2001. URL https://doi.org/10.1016/s0042-6989(01)00017-7. 71 [73] Granata, D., Carnevale, V. Accurate estimation of the intrinsic dimension using graph distances: Unraveling the geometric complexity of datasets. Scientific Reports, 6 (1), ago. 2016. URL https://doi.org/10.1038/srep31377. 83 [74] Spall, J. C. Implementation of the simultaneous perturbation algorithm for stochastic optimization. Aerospace and Electronic Systems, IEEE Transactions on, IEEE, 34, 817–823, 1998. 84 [75] Mayer, A., Mora, T., Rivoire, O., Walczak, A. M. Diversity of immune strategies explained by adaptation to pathogen statistics. PNAS, 113 (31), 8630–8635, 2016. 84 [76] Lenz, R., Carmona, P. L., Meer, P. The hyperbolic geometry of illumination-induced chromaticity changes. En: 2007 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 2007. URL https://doi.org/10.1109/cvpr.2007. 383212. 86 [77] Farup, I. Hyperbolic geometry for colour metrics. Optics Express, 22 (10), 12369, mayo 2014. URL https://doi.org/10.1364/oe.22.012369. 86 [78] Berthier, M., Provenzi, E. From riemannian trichromacy to quantum color opponency via hyperbolicity. Journal of Mathematical Imaging and Vision, feb. 2021. URL https://doi.org/10.1007/s10851-021-01023-5. 86 [79] Berthier, M., Provenzi, E. The quantum nature of color perception: Uncertainty relations for chromatic opposition. Journal of Imaging, 7 (2), 40, feb. 2021. URL https://doi.org/10.3390/jimaging7020040. 86 [80] Provenzi, E. On the issue of linearity in chromatic induction by a uniform background. Coloration Technology, 137 (1), 68–71, nov. 2020. URL https://doi.org/10.1111/cote.12507. 86 [81] Wyszecki, G., Fielder, G. H. New color-matching ellipses. Journal of the Optical Society of America, 61 (9), 1135–1152, 1971. 86, 147 [82] Alfvin, R. L., Fairchild, M. D. Cobserver variability in metameric color matches using color reproduction media. Color Research & Application, 22 (3), 530–539, 1997. [83] Fairchild, M. D., Heckaman, R. L. Metameric observers: A monte carlo approach. Color and Imaging Conference, 2013 (1), 185–190, 2013. URL https://www.ingentaconnect.com/content/ist/cic/2013/00002013/00000001/art00033. [84] Fairchild, M. D., Heckaman, R. L. Measuring observer metamerism: The nimeroff approach. Color Research & Application, 41 (2), 115–124, 2016. URL https://onlinelibrary.wiley.com/doi/abs/10.1002/col.21954. [85] Asano, Y., Fairchild, M. D., Blond´e, L., Morvan, P. Color matching experiment for highlighting interobserver variability. Color Research and Application, 41 (15), 530–539, 2016. [86] Asano, Y., Fairchild, M. D., Blond´e, L. Individual colorimetric observer model. PLoS ONE, 11 (2), 1–19, 02 2016. URL https://doi.org/10.1371/journal. pone.0145671. 86 [87] da Fonseca, M., Vattuone, N., Clavero, F., Echeveste, R., Samengo, I. The subjective metric of remembered colors: A fisher-information analysis of the geometry of human chromatic memory. PLOS ONE, 14, 1–30, 01 2019. URL https://doi.org/ 10.1371/journal.pone.0207992. 87, 148 [88] Zeki, S. Colour coding in the cerebral cortex: The responses of wavelength-selective and colour-coded cells in monkey visual cortex to changes in wavelength composition. Neuroscience, 9 (4), 767–781, ago. 1983. URL https://doi.org/10.1016/ 0306-4522(83)90266-x. 88 [89] Schein, S., Desimone, R. Spectral properties of v4 neurons in the macaque. The Journal of Neuroscience, 10 (10), 3369–3389, oct. 1990. URL https://doi.org/10.1523/jneurosci.10-10-03369.1990. [90] Wachtler, T., Sejnowski, T. J., Albright, T. D. Representation of color stimuli in awake macaque primary visual cortex. Neuron, 37 (4), 681–691, feb. 2003. URL https://doi.org/10.1016/s0896-6273(03)00035-7. 88 [91] Churchland, P. Chimerical colors: some phenomenological predictions from cognitive neuroscience. Philosophical Psychology, 18 (5), 527–560, oct. 2005. URL https://doi.org/10.1080/09515080500264115. 88 [92] Danilova, M., Mollon, J. Is discrimination enhanced at a category boundary? the case of unique red. JOSA A, 33 (3), A260–A266, 2016. 103, 105, 118 [93] Whorf, B. L. Language, thought, and reality. John b. carroll ed´on. Technology Press of MIT., 1956. 104 [94] Pinker, S. The language instinct. 1a ed´on. W. Morrow and Co, 1994. 104 [95] Wolff, P., Holmes, K. J. Linguistic relativity. Wiley Interdisciplinary Reviews: Cognitive Science, 2 (3), 253–265, oct. 2010. URL https://doi.org/10.1002/ wcs.104. 104 [96] Gladstone, W. E. Studies on Homer and the Homeric Age. Cambridge University Press, 1858. 104 [97] Brown, R. W., Lenneberg, E. H. A study in language and cognition. The Journal of Abnormal and Social Psychology, 49 (3), 454–462, 1954. URL https://doi.org/10.1037/h0057814. 104 [98] Roberson, D., Hanley, J. R., Pak, H. Thresholds for color discrimination in english and korean speakers. Cognition, 112 (3), 482–487, sep. 2009. URL https://doi.org/10.1016/j.cognition.2009.06.008. 104 [99] Boroditsky, L. Does language shape thought?: Mandarin and english speakers' conceptions of time. Cognitive Psychology, 43 (1), 1–22, ago. 2001. URL https://doi.org/10.1006/cogp.2001.0748. 105 [100] Loftus, E. F., Palmer, J. C. Reconstruction of automobile destruction: An example of the interaction between language and memory. Journal of Verbal Learning and Verbal Behavior, 13 (5), 585–589, oct. 1974. URL https://doi.org/10.1016/s0022-5371(74)80011-3. 105 [101] Kay, P., Kempton, W. What is the sapir-whorf hypothesis? American Anthropologist, 86 (1), 65–79, mar. 1984. URL https://doi.org/10.1525/aa.1984.86. 1.02a00050. 105 [102] Winawer, J., Witthoft, N., Frank, M. C., Wu, L., Wade, A. R., Boroditsky, L. Russian blues reveal effects of language on color discrimination. Proceedings of the National Academy of Sciences, 104 (19), 7780–7785, abr. 2007. URL https://doi.org/10.1073/pnas.0701644104. 105 [103] Regier, T., Kay, P., Cook, R. S. Focal colors are universal after all. Proceedings of the National Academy of Sciences, 102 (23), 8386–8391, mayo 2005. URL https://doi.org/10.1073/pnas.0503281102. 105 [104] MacLeod, D. I. A., Boynton, R. M. Chromaticity diagram showing cone excitation by stimuli of equal luminance. Journal of the Optical Society of America, 69 (8), 1183, ago. 1979. URL https://doi.org/10.1364/josa.69.001183. 106, 111 [105] Nagy, A. L., Doyal, J. A. Red–green color discrimination as a function of stimulus field size in peripheral vision. Journal of the Optical Society of America A, 10 (6), 1147, jun. 1993. URL https://doi.org/10.1364/josaa.10.001147.111 [106] Siegel, M. H. Color discrimination as a function of exposure time. Journal of the Optical Society of America, 55 (5), 566, mayo 1965. URL https://doi.org/10.1364/josa.55.000566. 111 [107] Brown, W. R. J. The influence of luminance level on visual sensitivity to color differences. Journal of the Optical Society of America, 41 (10), 684, oct. 1951. URL https://doi.org/10.1364/josa.41.000684. 112 [108] Gibson, J. J., Radner, M. Adaptation, after-effect and contrast in the perception of tilted lines. i. quantitative studies. Journal of Experimental Psychology, 20 (5), 453– 467, mayo 1937. URL https://doi.org/10.1037/h0059826. 123 [109] Webster, M. A., Mollon, J. Adaptation and the color statistics of natural images. Vision Research, 37 (23), 3283–3298, dic. 1997. URL https://doi.org/10.1016/s0042-6989(97)00125-9. 124 [110] Song, A., Faugeras, O., Veltz, R. A neural field model for color perception unifying assimilation and contrast. PLOS Computational Biology, 15 (6), e1007050, jun. 2019. URL https://doi.org/10.1371/journal.pcbi.1007050. 126 [111] Wright,W. D., Pitt, F. H. G. Hue discrimination in normal colour vision. Proceedings of the Physical Society, 46 (3), 459–473, 1934. 147 [112] Holtsmark, T. Colour discrimination and hue. Nature, 224 (5217), 366–367, 1969. [113] Pokorny, J., Smith, V. C. Wavelength discrimination in the presence of added chromatic fields. Journal of the Optical Society of America, 60 (4), 562–569, 1970. 147 [114] Heider, E. R., Olivier, D. C. The structure of the color space in naming and memory for two languages. Cognitive Psychology, 3 (2), 337–354, abr. 1972. URL https://doi.org/10.1016/0010-0285(72)90011-4. 147, 148, 159 [115] Kay, P., Regier, T. Resolving the question of color naming universals. Proceedings of the National Academy of Science or the United States of America, 100 (15), 9085–9089, 2003. [116] Brown, A. M., Lindsey, D. T., Guckes, K. M. G. Color names, color categories, and color-cued visual search: Sometimes, color perception is not categorical. Journal of Vision, 11 (2), 1–21, 2011. 147 [117] Bornstein, M. H. Name codes and color memory. The American Journal of Psychology, 89 (2), 269, jun. 1976. URL https://doi.org/10.2307/1421410. 147, 148, 159 [118] Bornstein, M. H., Korda, N. O. Discrimination and matching within and between hues measured by reaction times: Some implications for categorical perception and levels of information processing. Psychological Research, 46 (3), 207–222, 1984. 148 [119] Boynton, R. M., Fargo, L., Olson, C. X., Smallman, H. S. Category effects in color memory. Color Research & Application, 14 (5), 229–234, oct. 1989. URL https://doi.org/10.1002/col.5080140505. 148, 159 [120] Uchikawa, K., Shinoda, H. Influence of basic color categories on color memory discrimination. Color Research & Application, 21 (6), 430–439, dic. 1996. URL https://doi.org/10.1002/(sici)1520-6378(199612)21:6<430::aid-col5>3.0.co;2-x. 148, 159 [121] Roberson, D., Davidoff, J., Davies, I. R., Shapiro, L. R. The development of color categories in two languages: A longitudinal study. Journal of Experimental Psychology: General, 133 (4), 554–571, 2005. 147 [122] O¨ zgen, E., L., D. I. R. Acquisition of categorical color perception: A perceptual learning approach to the linguistic relativity hypothesis. Journal of Experimental Psychology: General, 131 (4), 477–493, 2002. [123] Pilling, M., Wiggett, A., O¨ zgen, E., Davies, I. R. L. Is color “categorical perception” really perceptual? Memory & Cognition, 31 (4), 538–551, jun. 2003. URL https://doi.org/10.3758/bf03196095. 147, 148, 159 [124] Witzel, C., Gegenfurtner, K. R. Categorical perception for red and brown. Journal of Experimental Psychology: Human Perception and Performance, 42 (4), 540–570, abr. 2016. URL https://doi.org/10.1037/xhp0000154. 147 [125] Witzel, C., Gegenfurtner, K. R. Categorical sensitivity to color differences. Journal of Vision, 13 (7(1)), 1–33, 2013. 147, 152, 164 [126] Witzel, C., Gegenfurtner, K. R. Categorical facilitation with equally discriminable colors. Journal of Vision, 15 (8), 22, jun. 2015. URL https://doi.org/10. 1167/15.8.22. 147 [127] Brouwer, G. J., Heeger, D. J. Categorical clustering of the neural representation of color. The Journal of Neuroscience, 33 (39), 15454–15465, sep. 2013. URL https://doi.org/10.1523/jneurosci.2472-13.2013. 148 [128] Koida, K., Komatsu, H. Effects of task demands on the responses of color-selective neurons in the inferior temporal cortex. Nature Neuroscience, 10 (1), 108–116, 2007. 148 [129] Webster, M. A., Kay, P. Color categories and color appearance. Cognition, 122 (3), 175–392, 2012. 148 [130] Huette, S. Encyclopedia of Color Science and Technology, cap. Dynamics of Color Category Formation and Boundaries, p´ags. 1–5. New York: Springer Science and Business Media, 2012. 148 [131] Dennet, D. D. Consciousness explained. London: Penguin Science, 1993. 148 [132] Roberson, D., Davies, I., Davidoff, J. Color categories are not universal: Replications and new evidence from a stone-age culture. Journal of Experimental Psychology: General, 129 (3), 369–398, 2000. URL https://doi.org/10.1037/ 0096-3445.129.3.369. 148, 159 [133] Bae, G.-Y., Olkkonen, M., Allred, S. R.,Wilson, C., Flombaum, J. I. Stimulus-specific variability in color working memory with delayed estimation. Journal of Vision, 14 (4), 7–7, abr. 2014. URL https://doi.org/10.1167/14.4.7. 152, 164 [134] Bae, G.-Y., Olkkonen, M., Allred, S. R., Flombaum, J. I. Why some colors appear more memorable than others: A model combining categories and particulars in color working memory. Journal of Experimental Psychology: General, 144 (4), 744–763, ago. 2015. URL https://doi.org/10.1037/xge0000076. 148, 159, 160 [135] Amari, S. I., Nagaoka, H. Methods in information Geometry. Oxford: Oxford University Press, 2000. 149 [136] Nemes, V. A., Parry, N. R. A., McKeefry, D. J. A behavioural investigation of human visual short term memory for colour. Ophthalmic and Physiological Optics, 30 (5), 594–601, ago. 2010. URL https://doi.org/10.1111/j.1475-1313.2010.00772.x. 150, 152 [137] Nemes, V. A., Parry, N. R. A., Whitaker, D., McKeefry, D. J. The retention and disruption of color information in human short-term visual memory. Journal of Vision, 12 (1), 26–26, ene. 2012. URL https://doi.org/10.1167/12.1.26. 150 [138] Tabachnick, B., Parducci, A. Improved recognition with feedback: Discriminatety and range-frequency effects. Bulletin of the Psychonomic Society, 1 (1), 56–58, ene. 1973. URL https://doi.org/10.3758/bf03333339. 151 [139] Gravesen, J. The metric of colour space. Graphical Models, 82, 77–86, nov. 2015. URL https://doi.org/10.1016/j.gmod.2015.06.005. 152 [140] Romero, J., Garc´ıa, J. A., del Barco, L. J., Hita, E. Evaluation of color-discrimination ellipsoids in two-color spaces. JOSA A, 10 (5), 827–837, 1993. 152 [141] Brown, W. R. J. Color discrimination of twelve observers. Journal of the Optical Society of America, 47 (2), 137, feb. 1957. URL https://doi.org/10.1364/josa.47.000137. [142] Webster, M. A., Miyahara, E., Malkoc, G., Raker, V. E. Variations in normal color vision i cone-opponent axes. Journal of the Optical Society of America A, 17 (9), 1535, sep. 2000. URL https://doi.org/10.1364/josaa.17.001535. 152 [143] Cram´er, H. A contribution to the theory of statistical estimation. Scandinavian Actuarial Journal, 1946 (1), 458–463, 1946. 164 [144] Cover, T. M., Thomas, J. A. Elements of Information Theory. New York:Wiley, 1991. 164 [145] Farnsworth, D. The farnsworth-munsell 100-hue and dichotomous tests for color vision. Journal of the Optical Society of America, 33 (10), 568–574, 1943. 173 |
| Materias: | Medicina > Neurociencias |
| Divisiones: | Gcia. de área de Investigación y aplicaciones no nucleares > Gcia. de Física > Física médica |
| Código ID: | 1047 |
| Depositado Por: | Tamara Cárcamo |
| Depositado En: | 13 Jun 2022 15:01 |
| Última Modificación: | 13 Jun 2022 15:01 |
Personal del repositorio solamente: página de control del documento
