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Pathways of Light

  • V. Srinivasa Chakravarthy
Chapter

Abstract

This chapter is about the problem of vision, which has, interestingly, two subproblems. One of these subproblems is an easy one, the other hard. The easy problem of vision concerns itself with what happens to light when it enters the brain through the portals called eyes. What is its path? What are the major stopovers? What exactly happens at each of these stopovers? The problem is not easy because it is known in all its immense detail. In fact, the details of the visual system are not completely unraveled, despite the intense and sometimes disproportionate attention paid to vision by the neuroscience community. It is easy because the problem is mainly one of getting all the relevant details by expending adequate resources, human and otherwise, and a lot of time. It is easy in the sense that there is a method to go about it. The other problem of vision is not so easy because there is no well-defined method that allows you to make predictable progress in that area. The hard problem of vision deals with the more interesting, popular question: how do we see? What are the exact neural events that conspire to enable us to have the moment-to-moment revelation of a moving, multicolored vision of the universe? It is not that neuroscience failed to make any progress in this matter. It is just that this second problem resides on the borders of science and philosophy, leading us on into deeper questions regarding the nature of consciousness and so on. The standard evidence-based methods of science seem to flounder and buckle in tacking the second problem.

References

  1. Ali, M., & Klyne, A. (1985). Vision in vertebrates. New York: Plenum Press.CrossRefGoogle Scholar
  2. Arditi, A. R., Anderson, P. A., & Movshon, J. A. (1981). Monocular and binocular detection of moving sinusoidal gratings. Vision Research, 21(3), 329–336.CrossRefGoogle Scholar
  3. Baker, C. L., Hess, R. F., & Zihl, J. (1991). Residual motion perception in a “motion-blind” patient, assessed with limited-lifetime random dot stimuli. Journal of Neuroscience, 11(2), 454–461.CrossRefGoogle Scholar
  4. Blasdel, G. G. (1992a). Orientation selectivity, preference, and continuity in monkey striate cortex. Journal of Neuroscience, 12(8), 3139–3161.CrossRefGoogle Scholar
  5. Blasdel, G. G. (1992b). Differential imaging of ocular dominance and orientation selectivity in monkey striate cortex. Journal of Neuroscience, 12(8), 3115–3138.CrossRefGoogle Scholar
  6. Conover, E. (2016). Human eye spots single photons. Science News. Retrieved 2016-08-02.Google Scholar
  7. Darwin, C. (1859). On the origin of species (p. 172) (quote on the evolution of the eye).Google Scholar
  8. Dawkins, R. (1986). The blind watchmaker: Why the evidence of evolution reveals a universe without design (p. 93). New York: W.W. Norton and Company.Google Scholar
  9. Ellis, H. D., & Florence, M. (1990). Bodamer’s (1947) paper on prosopagnosia. Cognitive Neuropsychology, 7(2), 81–105.CrossRefGoogle Scholar
  10. Futterman, S. (1975). Metabolism and photochemistry in the retina. In R. A. Moses (Ed.), Adler’s physiology of the eye (6th ed., pp. 406–419). St. Louis: C.V. Mosby Company.Google Scholar
  11. Gibson, E. J., & Pick, A. D. (2000). An ecological approach to perceptual learning and development. USA: Oxford University Press.Google Scholar
  12. Goodale, M. A., & Milner, A. D. (1992). Separate visual pathways for perception and action. Trends in Neurosciences, 15(1), 20–25.CrossRefGoogle Scholar
  13. Gross, C. G. (1973). Visual functions of inferotemporal cortex. In Visual centers in the brain (pp. 451–482). Berlin, Heidelberg: Springer.CrossRefGoogle Scholar
  14. Haxby, J. V., Grady, C. L., Horwitz, B., Ungerleider, L. G., Mishkin, M., Carson, R. E., … Rapoport, S. I. (1991). Dissociation of object and spatial visual processing pathways in human extrastriate cortex. Proceedings of the National Academy of Sciences, 88(5), 1621–1625.CrossRefGoogle Scholar
  15. Hegdé, J., & Van Essen, D. C. (2000). Selectivity for complex shapes in primate visual area V2. Journal of Neuroscience, 20(5), RC61.CrossRefGoogle Scholar
  16. Ito, M., & Komatsu, H. (2004). Representation of angles embedded within contour stimuli in area V2 of macaque monkeys. Journal of Neuroscience, 24(13), 3313–3324.CrossRefGoogle Scholar
  17. Kreimer, G. (2009). The green algal eyespot apparatus: A primordial visual system and more?. Current Genetics, 55(1), 19–43.  https://doi.org/10.1007/s00294-008-0224-8. PMID 19107486.CrossRefGoogle Scholar
  18. Kriegeskorte, N., Mur, M., Ruff, D. A., Kiani, R., Bodurka, J., Esteky, H., … Bandettini, P. A. (2008). Matching categorical object representations in inferior temporal cortex of man and monkey. Neuron, 60(6), 1126–1141.CrossRefGoogle Scholar
  19. Le Vay, S., Wiesel, T. N., & Hubel, D. H. (1980). The development of ocular dominance columns in normal and visually deprived monkeys. Journal of Comparative Neurology, 191(1), 1–51.CrossRefGoogle Scholar
  20. Lindberg, D. C. (1981). Alhazen and the new intromission theory of vision. Theories of vision (Chapter 4, pp. 58–67). The University of Chicago Press.Google Scholar
  21. Marr, D., & Poggio, T. (1976). Cooperative computation of stereo disparity. Science, 194(4262), 283–287.CrossRefGoogle Scholar
  22. Mishkin, M., Ungerleider, L. G., & Macko, K. A. (1983). Object vision and spatial vision: Two cortical pathways. Trends in Neurosciences, 6, 414–417.CrossRefGoogle Scholar
  23. Nilsson, D.-E., & Pelger, S. (1994). A pessimistic estimate of the time required for an eye to evolve. Proceedings of the Royal Society of London, Series B: Biological Sciences, 256(1345), 53–58.CrossRefGoogle Scholar
  24. Pack, C. C., & Born, R. T. (2001). Temporal dynamics of a neural solution to the aperture problem in visual area MT of macaque brain. Nature, 409(6823), 1040.CrossRefGoogle Scholar
  25. Robertson, L., Treisman, A., Friedman-Hill, S., & Grabowecky, M. (1997). The interaction of spatial and object pathways: Evidence from Balint’s syndrome. Journal of Cognitive Neuroscience, 9(3), 295–317.CrossRefGoogle Scholar
  26. Sacks, O. (1996). To see or not to see. In An anthropologist on mars (pp. 108–152). New York: Random House.Google Scholar
  27. Savino, P. J., & Danesh-Meyer, H. V. (2012). Color atlas and synopsis of clinical ophthalmology—Wills Eye Institute—Neuro-ophthalmology (p. 12). Philadelphia: Lippincott Williams & Wilkins. ISBN 978-1-60913-266-8. Retrieved November 9, 2014.Google Scholar
  28. Sim, N., Cheng, M. F., Bessarab, D., Jones, C. M., & Krivitsky, L. A. (2012). Measurement of photon statistics with live photoreceptor cells. Physical Review Letters, 109, 113601.Google Scholar
  29. Sperry, R. W. (1950). Neural basis of the spontaneous optokinetic response produced by visual inversion. Journal of comparative and physiological psychology, 43(6), 482.CrossRefGoogle Scholar
  30. Tanaka, K. (1993). Neuronal mechanisms of object recognition. Science, 262(5134), 685–688.CrossRefGoogle Scholar
  31. Tessier-Lavigne, M. Visual processing by the retina. In E. R. Kandel, J. H. Schwartz, & T. M. Jessell (Eds.), Principles of neural science (Vol. 4, Chapter 26). New York: McGraw-Hill.Google Scholar
  32. Wong, D., & Kwen, B. H. (2005). Shedding light on the nature of science through a historical study of light, redesigning pedagogy: Research, policy, practice.Google Scholar
  33. Wurtz, R. H., & Kandel, E. R. Central visual pathways. In E. R. Kandel, J. H. Schwartz, & T. M. Jessell (Eds.), Principles of neural science (Vol. 4, Chapter 27). New York: McGraw-Hill.Google Scholar
  34. Young, M. P., & Yamane, S. (1992). Sparse population coding of faces in the inferotemporal cortex. Science, 256(5061), 1327–1331.CrossRefGoogle Scholar
  35. Zeki, S. (1990). A century of cerebral achromatopsia. Brain, 113(6), 1721–1777.CrossRefGoogle Scholar
  36. Zeki, S. (1991). Cerebral akinetopsia (visual motion blindness): A review. Brain, 114(2), 811–824.CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Indian Institute of Technology MadrasChennaiIndia

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