Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects (original) (raw)

References

  1. Hubel, D. H. & Wiesel, T. N. Receptive fields and functional architecture in two non-striate visual areas (18 and 19) of the cat. J. Neurophysiol. 28, 229–289 (1965).
    Article CAS Google Scholar
  2. Hubel, D. H. & Wiesel, T. N. Receptive fields and functional architecture of monkey striate cortex . J. Physiol. (Lond.) 195, 215–243 (1968).
    Article CAS Google Scholar
  3. Bolz, J. & Gilbert, C. D. Generation of end-inhibition in the visual cortex via interlaminar connections. Nature 320, 362–365 (1986).
    Article CAS Google Scholar
  4. Hubel, D. H. & Livingstone, M. S. Segregation of form, color, and stereopsis in primate area 18. J. Neurosci. 7, 3378–3415 (1987).
    Article CAS Google Scholar
  5. Desimone, R. & Schein, S. J. Visual properties of neurons in area V4 of the macaque: sensitivity to stimulus form. J. Neurophysiol. 57, 835–868 ( 1987).
    Article CAS Google Scholar
  6. Allman, J., Miezin, F. & McGuinness, E. Stimulus specific responses from beyond the classical receptive field: Neurophysiological mechanisms for local-global comparisons in visual neurons. Annu. Rev. Neurosci. 8, 407–429 (1985).
    Article CAS Google Scholar
  7. Dobbins, A., Zucker, S. W. & Cynader, M. S. Endstopped neurons in the visual cortex as a substrate for calculating curvature. Nature 329, 438 –441 (1987).
    Article CAS Google Scholar
  8. Bolz, J., Gilbert, C. D. & Wiesel, T. N. Pharmacological analysis of cortical circuitry. Trends Neurosci. 12, 292–296 (1989).
    Article CAS Google Scholar
  9. Peterhans, E. & von der Heydt, R. in Representations of Vision. Trends and Tacit Assumptions (eds Gorea, A., Frégnac, Y., Kapoulis, Z. & Findlay, J.) 111–124 (Cambridge Univ. Press, Cambridge, UK, 1991).
    Google Scholar
  10. Grossberg, S., Mingolla, E. & Ross, W. D. Visual brain and visual perception: how does the cortex do perceptual grouping? Trends Neurosci. 20, 106–111 (1997).
    Article CAS Google Scholar
  11. Peterhans, E. & von der Heydt, R. Subjective contours—bridging the gap between psychophysics and physiology. Trends Neurosci. 14, 112–119 ( 1991).
    Article CAS Google Scholar
  12. Rao, R. P. N. & Ballard, D. H. Dynamic model of visual recognition predicts neural response properties in the visual cortex. Neural Comput. 9, 721–763 ( 1997).
    Article CAS Google Scholar
  13. Gallant, J. L., Connor, C. E. & Van Essen, D. C. Neural activity in areas V1, V2 and V4 during free viewing of natural scenes compared to controlled viewing. Neuroreport 9, 2153–2158 ( 1998).
    Article CAS Google Scholar
  14. Attneave, F. Some informational aspects of visual perception. Psychol. Rev. 61, 183–193 ( 1954).
    Article CAS Google Scholar
  15. MacKay, D. M. in Automata Studies (eds Shannon, C. E. & McCarthy, J.) 235– 251 (Princeton Univ. Press, Princeton, NJ, 1956).
    Google Scholar
  16. Barlow, H. B. in Sensory Communication (ed. Rosenblith, W. A.) 217– 234 (MIT Press, Cambridge, MA, 1961).
    Google Scholar
  17. Atick, J. J. Could information theory provide an ecological theory of sensory processing? Network Comput. Neural Sys. 3, 213– 251 (1992).
    Article Google Scholar
  18. Buchsbaum, G. & Gottschalk, A. Trichromacy, opponent colours coding and optimum colour information transmission in the retina. Proc. R. Soc. Lond. B Biol. Sci. 220, 89– 113 (1983).
    Article CAS Google Scholar
  19. Srinivasan, M. V., Laughlin, S. B. & Dubs A. Predictive coding: A fresh view of inhibition in the retina. Proc. R. Soc. Lond. B Biol. Sci. 216, 427–459 (1982).
    Article CAS Google Scholar
  20. Dan, Y., Atick, J. J. & Reid, R. C. Efficient coding of natural scenes in the lateral geniculate nucleus: experimental test of a computational theory. J. Neurosci. 16, 3351–3362 (1996).
    Article CAS Google Scholar
  21. Dong, D. W. & Atick, J. J. Temporal decorrelation: a theory of lagged and nonlagged responses in the lateral geniculate nucleus. Network Comput. Neural Sys. 6, 159– 178 (1995).
    Article Google Scholar
  22. Mumford, D. On the computational architecture of the neocortex. II. The role of cortico-cortical loops. Biol. Cybern. 66, 241– 251 (1992).
    Article CAS Google Scholar
  23. Pece, A. E. C. in Artificial Neural Networks 2 (eds Aleksander, I. & Taylor, J.) 865–868 (Elsevier, Amsterdam, 1992).
    Book Google Scholar
  24. Softky, W. R. in Advances in Neural Information Processing Systems 8 (eds Touretzky, D., Mozer, M. & Hasselmo, M.) 809–815 (MIT Press, Cambridge, MA, 1996).
    Google Scholar
  25. Ullman, S. in Large-Scale Neuronal Theories of the Brain (eds Koch, C. & Davis, J. L.) 257–270 (MIT Press, Cambridge, MA, 1994).
    Google Scholar
  26. Olshausen, B. A. & Field, D. J. Sparse coding with an overcomplete basis set: A strategy employed by V1? Vision Res. 37, 3311–3325 ( 1997).
    Article CAS Google Scholar
  27. Dayan, P., Hinton, G.E., Neal, R.M. & Zemel, R.S. The Helmholtz machine. Neural Comput. 7, 889– 904, (1995).
    Article CAS Google Scholar
  28. Luettgen, M. R. & Willsky, A. S. Likelihood calculation for a class of multiscale stochastic models, with application to texture discrimination. IEEE Trans. Image Proc. 4, 194–207 (1995).
    Article CAS Google Scholar
  29. Felleman, D. J. & Van Essen, D. C. Distributed hierarchical processing in the primate cerebral cortex. Cereb. Cortex 1, 1–47 ( 1991).
    Article CAS Google Scholar
  30. Field, D. J. Relations between the statistics of natural images and the response properties of cortical cells. J. Opt. Soc. Am. A 4, 2379–2394 (1987).
    Article CAS Google Scholar
  31. Bell, A. J. & Sejnowski, T. J. The "independent components" of natural scenes are edge filters. Vision Res. 37, 3327–3338 (1997).
    Article CAS Google Scholar
  32. Olshausen, B. A. & Field, D. J. Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature 381, 607– 609 (1996).
    Article CAS Google Scholar
  33. Zipser, K., Lamme, V. A. F. & Schiller, P. H. Contextual modulation in primary visual cortex. J. Neurosci. 16, 7376–7389 (1996).
    Article CAS Google Scholar
  34. Sandell, J. H. & Schiller, P. H. Effect of cooling area 18 on striate cortex cells in the squirrel monkey. J. Neurophysiol. 48, 38–48 (1982).
    Article CAS Google Scholar
  35. Knierim, J. & Van Essen, D. C. Neural responses to static texture patterns in area V1 of the alert macaque monkey. J. Neurophysiol. 67, 961–980 ( 1992).
    Article CAS Google Scholar
  36. Sillito, A. M., Grieve, K. L., Jones, H. E., Cudeiro, J. & Davis, J. Visual cortical mechanisms detecting focal orientation discontinuities. Nature 378, 492–496 (1995).
    Article CAS Google Scholar
  37. Hupé, J. M. et al. Cortical feedback improves discrimination between figure and background by V1, V2 and V3 neurons. Nature 394 , 784–787 (1998).
    Article Google Scholar
  38. Murphy, P. C. & Sillito, A. M. Corticofugal feedback influences the generation of length tuning in the visual pathway. Nature 329, 727–729 (1987).
    Article CAS Google Scholar
  39. Gilbert, C. D. Adult cortical dynamics. Physiol. Rev. 78, 467–485 (1998).
    Article CAS Google Scholar
  40. Lee, D. D. & Seung, H. S. in Advances in Neural Information Processing Systems 9 (eds Mozer, M., Jordan, M. & Petsche, T.) 515–521 (MIT Press, Cambridge, MA, 1997).
    Google Scholar
  41. Heeger, D. J., Simoncelli, E. P. & Movshon, J. A. Computational models of cortical visual processing. Proc. Natl. Acad. Sci. USA 93, 623– 627 (1996).
    Article CAS Google Scholar
  42. Miller, E. K., Li, L. & Desimone, R. A neural mechanism for working and recognition memory in inferior temporal cortex. Science 254, 1377–1379 (1991).
    Article CAS Google Scholar
  43. Gross, C. G. & Sergent, J. Face recognition. Curr. Opin. Neurobiol. 2, 156–161 (1992).
    Article CAS Google Scholar
  44. Logothetis, N. K. & Pauls, J. Psychophysical and physiological evidence for viewer-centered object representations in the primate. Cereb. Cortex 5, 270–288 (1995).
    Article CAS Google Scholar
  45. Poggio, T. & Edelman, S. A network that learns to recognize 3D objects. Nature 343, 263– 266 (1990).
    Article CAS Google Scholar
  46. Bell, C., Bodznick, D., Montgomery, J. & Bastian, J. The generation and subtraction of sensory expectations within cerebellum-like structures. Brain Behav. Evol. 50 Suppl. 1, 17–31 (1997).
    Article Google Scholar
  47. Schultz, W. et al. in Models of Information Processing in the Basal Ganglia (eds Houk, J. C., Davis, J. L. & Beiser, D. G.) 233– 248 (MIT Press, Cambridge, MA, 1995).
    Google Scholar
  48. Creutzfeldt, O. D. Generality of the functional structure of the neocortex. Naturwissenschaften 64, 507–517 ( 1977).
    Article CAS Google Scholar
  49. Rao, R. P. N. An optimal estimation approach to visual perception and learning. Vision Res. (in press).
  50. Rissanen, J. Stochastic Complexity in Statistical Inquiry (World Scientific, Singapore, 1989).
    Google Scholar

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