Volume 13 · Number 1 · Pages 117–125

< Previous Paper · Next Paper >

Missing Colors: The Enactivist Approach to Perception

Adrián G. Palacios, María-José Escobar & Esteban Céspedes

Download the full text in
PDF (1059 kB)

> Citation > Similar > References > Add Comment


Context: Part of Varela’s work focused on the study of visual perception, particularly on the grounds of an enactivist theory of vision. Problem: Varela held that the problem of misrepresentation and the comparability of visual experience were crucial. We live with other creatures in sensory worlds that are not tractable, so could we share color-similar experiences? We are still missing an integrative enactive framework to tackle the problems of misrepresentation and comparability related to animal color experience. Method: We carried out a literature survey to draw attention to the status of the enactivist theory of vision and to explore how the problems of misrepresentation and comparability may be tackled. Results: As shown, philosophy and computational science have recently incorporated concepts from neurobiology that close gaps between disciplines and support aspects of the enactivist approach of vision. Implications: Epistemological problems related to perception are here tackled, considering some controversial assumptions related to vision. We argue that an enactivist theory of visual perception may not only clarify the problematic consequences of those assumptions, but also fruitfully guide future philosophical and empirical research on this topic. Constructivist content: The presence of singular “visual channels”, as well as physical, sensorimotor and evolutionary factors, constrains our own perceptual experience as proposed by enactivism.

Key words: Enaction, perception, misrepresentation, comparability, high color space dimensionality, objectivism, subjectivism, computational science


Palacios A. G., Escobar M.-J. & Céspedes E. (2017) Missing colors: The enactivist approach to perception. Constructivist Foundations 13(1): 117–125. http://constructivist.info/13/1/117

Export article citation data: Plain Text · BibTex · EndNote · Reference Manager (RIS)

Similar articles

Palacios A. G., Escobar M.-J. & Céspedes E. (2017) Authors’ Response: Is a Weak Notion of Representation not Compatible with a Contextualist and Enactivist Account of Perception?

Hawes R. (2013) Art & Neurophenomenology: Putting the Experience Before the Words

Staude M. (2008) Meaning and Description in Non-dualism: A Formalization and Extension

Werner K. (2017) Coordination Produces Cognitive Niches, not just Experiences: A Semi-Formal Constructivist Ontology Based on von Foerster

Maturana H. R. (2012) Reflections on My Collaboration with Francisco Varela


Adelson E. H. (2000) Lightness perception and lightness illusions. In: Gazzaniga M. (ed.) the new cognitive neurosciences. Second edition. MIT Press, Cambridge MA: 339–351. << Google Scholar

Allen M. & Friston K. (2016) From cognitivism to autopoiesis: Towards a computational framework for the embodied mind. Synthese: First Online. Available at http://cepa.info/4099

Awh E., Belopolsky A. V. & Theeuwes J. (2012) Top-down versus bottom-up attentional control: A failed theoretical dichotomy. Trends in Cognitive Sciences 16(8): 437–443. << Google Scholar

Bishop R. & Atmanspacher H. (2006) Contextual emergence in the description of properties. Foundations of Physics 36(12): 1753–1777. << Google Scholar

Bompas A. & O’Regan J. K. (2006) Evidence for a role of action in colour perception. Perception 35(1): 65–78. << Google Scholar

Bradley P. & Tye M. (2001) Of colors, kestrels, caterpillars, and leaves. The Journal of Philosophy 98(9): 469–487. << Google Scholar

Brainard D. H. & Freeman W. T. (1997) Bayesian color constancy. JOSA A 14(7): 1393–1411. << Google Scholar

Bruce N. D. B. & Tsotsos J. K. (2009) Saliency, attention, and visual search: An information theoretic approach. Journal of Vision 9(3): 5–5. << Google Scholar

Churchland P. (2007) On the reality (and diversity) of objective colors: How color-qualia space is a map of reflectance-profile space. Philosophy of Science 74(2): 119–149. << Google Scholar

Cohen J. (2003) Color: A functionalist proposal. Philosophical Studies 113(1): 1–42. << Google Scholar

Cohen J. (2004) Color properties and color ascriptions: A relationalist manifesto. The Philosophical Review 113(4): 451–506. << Google Scholar

Cohen J. (2009) The red and the real: An essay on color ontology. Oxford University Press. << Google Scholar

Crane T. (2001) Elements of mind: An Introduction to the Philosophy of Mind. Oxford University Press. << Google Scholar

Davidson D. (1970) Mental events. In: Foster L. & Swanson J. W. (eds.) Experience and theory. University of Massachusetts Press, Amherst: 79–101. << Google Scholar

de Croon G. C. H. E., Sprinkhuizen-Kuyper I. G. & Postma E. O. (2009) Comparing active vision models. Image and Vision Computing 27(4): 374–384. << Google Scholar

Ebner M. (2007) Color constancy. John Wiley & Sons, Chichester. << Google Scholar

Floreano D., Kato T., Marocco D. & Sauser E. (2004) Coevolution of active vision and feature selection. Biological Cybernetics 90(3): 218–228. << Google Scholar

Floreano D., Suzuki M. & Mattiussi C. (2005) Active vision and receptive field development in evolutionary robots. Evolutionary Computation 13(4): 527–544. << Google Scholar

Gallagher S. & Allen M. (2016) Active inference, enactivism and the hermeneutics of social cognition. Synthese, First Online. Available at http://cepa.info/4222

Gallagher S. (2008) Are minimal representations still representations? International Journal of Philosophical Studies 16(3): 351–369. << Google Scholar

Gehler P. V., Rother C., Blake A., Minka T. & Sharp T. (2008) Bayesian color constancy revisited. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR): 1–8. << Google Scholar

Gibson J. J. (1979) The ecological approach to visual perception. Houghton Mifflin, Boston. << Google Scholar

Gijsenij A., Gevers T. & van de Weijer J. (2011) Computational color constancy: Survey and experiments. IEEE Transactions on Image Processing 20(9): 2475–2489. << Google Scholar

Hardin C. L. (1988) Color for philosophers: Unweaving the rainbow. Hackett, Indianapolis IN. << Google Scholar

Högman V., Björkman M., Maki A. & Kragic D. (2016) A sensorimotor learning framework for object categorization. IEEE Transactions on Cognitive and Developmental Systems 8(1): 15–25. << Google Scholar

Hilbert D. R. (1992) What is color vision? Philosophical Studies 68(3): 351–370. << Google Scholar

Hugrass L., Slavikova J., Horvat M., Musawi A. A. & Crewther D. (2017) Temporal brightness illusion changes color perception of “the dress.” Journal of Vision 17(5): 6–7. << Google Scholar

Hutto D. D. & Myin E. (2012) Radicalizing enactivism. MIT Press, Cambridge MA. << Google Scholar

Knill D. C. & Pouget A. (2004) The Bayesian brain: The role of uncertainty in neural coding and computation. Trends in Neurosciences 27(12): 712–719. << Google Scholar

Kraft J. M. & Brainard D. H. (1999) Mechanisms of color constancy under nearly natural viewing. Proceedings of the National Academy of Sciences 96(1): 307–312. << Google Scholar

Levins R. & Lewontin R. C. (1985) The dialectical biologist. Harvard University Press, Cambridge MA. << Google Scholar

Lotto R. B. (2004) Visual development: Experience puts the colour in life. Current Biology 14(15): R619–R621. << Google Scholar

Maloney L. T. & Wandell B. A. (1986) Color constancy: A method for recovering surface spectral reflectance. Journal of the Optical Society of America A 3(1): 29–33. << Google Scholar

Marr D. (2010) Vision. MIT Press, Cambridge MA. << Google Scholar

Maturana H. R. & Varela F. J. (1973) De máquinas y seres vivos: Una teoría sobre la organización biológica. Editorial Universitaria, Santiago. Available at http://cepa.info/541

Morel J. M., Petro A. B. & Sbert C. (2009) Fast implementation of color constancy algorithms. In: Eschbach R., Marcu G. G., Tominaga S. & Rizzi A. (eds.) Proceedings SPIE 7241, Color imaging XIV: Displaying, processing, hardcopy, and applications: 724106. << Google Scholar

Noë A. & O’Regan J. K. (2002) On the brain-basis of visual consciousness: A sensorimotor account. In: Thompson E. & Noë A. (eds.) Vision and mind: Selected readings in the philosophy of perception. MIT Press, Cambridge MA: 567–598. << Google Scholar

Noë A. (2004) Action in perception. MIT Press, Cambridge MA. << Google Scholar

O’Regan J. K. & Noë A. (2001) A sensorimotor account of vision and visual consciousness. Behavioral and Brain Sciences 24(5): 939–973. << Google Scholar

Pouget A., Beck J. M., Ma W. J. & Latham P. E. (2013) Probabilistic brains: Knowns and unknowns. Nature Neuroscience 16(9): 1170–1178. << Google Scholar

Purves D., Lotto R. B., Williams S. M., Nundy S. & Yang Z. (2001) Why we see things the way we do: Evidence for a wholly empirical strategy of vision. Philosophical Transaction of the Royal Society of London 356: 285–297. << Google Scholar

Rasolzadeh B., Björkman M., Huebner K. & Kragic D. (2010) An active vision system for detecting, fixating and manipulating objects in the real world. The International Journal of Robotics Research 29(2–3): 133–154. << Google Scholar

Sabesan R., Schmidt B. P., Tuten W. S. & Roorda A. (2016) The elementary representation of spatial and color vision in the human retina. Science Advances 2(9): E1600797–e1600797. << Google Scholar

Smith A. D. (2002) The problem of perception. Harvard University Press, Cambridge MA. << Google Scholar

Song D., Ek C. H., Huebner K. & Kragic D. (2015) Task-based robot grasp planning using probabilistic inference. IEEE Transactions on Robotics 31(3): 546–561. << Google Scholar

Stricker M. & Michael S. (1994) The capacity of color histogram indexing. In: Proceedings of IEEE conference on computer vision and pattern recognition. Seattle WA: 704–708. << Google Scholar

Suzuki M. & Floreano D. (2008) Enactive robot vision. Adaptive Behavior 16(2–3): 122–128. << Google Scholar

Suzuki M., Floreano D. & Di Paolo E. A. (2005) The contribution of active body movement to visual development in evolutionary robots. Neural Networks 18(5–6): 656–665. << Google Scholar

Thompson E. (1995) Colour vision: A study in cognitive science and the philosophy of perception. Routledge, London. << Google Scholar

Thompson E., Palacios A. & Varela F. J. (1992) On the ways to color. Behavioral and Brain Sciences 15(1): 1–74. << Google Scholar

Varela F. J., Thompson E. & Rosch E. (1991) The embodied mind: cognitive science and human experience. MIT Press, Cambridge MA. << Google Scholar

Verschure P., Voegtlin T. & Douglas R. J. (2003) Environmentally mediated synergy between perception and behaviour in mobile robots. Nature 425(6958): 620–624. << Google Scholar

Viéville T. V. (1997) A few steps towards 3D active vision. Springer, New York. << Google Scholar

Wallisch P. (2017) Illumination assumptions account for individual differences in the perceptual interpretation of a profoundly ambiguous stimulus in the color domain: “The dress.” Journal of Vision 17(4): 5–14. << Google Scholar

Wheeler M. (2008) Minimal representing: A response to Gallagher. International Journal of Philosophical Studies 16(3): 371–376. << Google Scholar

Xiao B. (2016) Color constancy. In: Luo R. (ed.) Encyclopedia of color science and technology. Springer, New York: 281–290. << Google Scholar

Yuille A. & Kersten D. (2006) Vision as Bayesian inference: Analysis by synthesis? Trends in Cognitive Sciences 10(7): 301–308. << Google Scholar

Comments: 0

To stay informed about comments to this publication and post comments yourself, please log in first.