Processing of natural time series of intensities by the visual system of the blowfly

Vision Research

Volumn 37, Issue 23, 1997, Pages 3407-3416

  Van Hateren, J H ^a  

^a UNIVERSITY OF GRONINGEN   (Netherlands)

Author keywords

Gain control; LMC; Natural light intensities; Photoreceptor; Temporal power spectrum

Indexed keywords

ARTICLE; CONTRAST; CONTROL; FLY; HUMAN; INFORMATION PROCESSING; LIGHT; NERVE CELL; NONHUMAN; PHOTORECEPTOR; POWER SPECTRUM; PRIORITY JOURNAL; RETINA CONE; RETINA FOVEA; TIME; VISUAL SYSTEM;

EID: 0030828643     PISSN: 00426989     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0042-6989(97)00105-3     Document Type: Article

References (32)

1. Atick, J. J. (1992). Could information theory provide an ecological theory of sensory processing? Network, 3, 213-251.
2. Atick, J. J. & Redlich, A. N. (1990). Towards a theory of early visual processing. Neural Computation, 2, 308-320.
3. Bell, A. J. & Sejnowski, T. J. (1995). An information maximization approach to blind separation and blind deconvolution. Neural Computation, 7, 1129-1159.
4. Bialek, W., Ruderman, D. L. & Zee, A. (1991). Optimal sampling of natural images: a design principle for the visual system? In Lippmann, R. P., Moody, J. E. & Touretzky, D. S. (Eds), Neural information processing systems 3 (pp. 363-369). San Mateo: Morgan Kaufmann.
5. Burton, G. J. & Moorhead, I. R. (1987). Color and spatial structure in natural scenes. Applied Optics, 26, 157-170.
6. Dan, Y., Atick, J. J. & Reid, R. C. (1996). Efficient coding of natural scenes in the lateral geniculate nucleus: experimental test of a computational theory. Journal of Neuroscience, 16, 3351-3362.
7. DeValois, R. L. & DeValois, K. K. (1988). Spatial vision. New York: Oxford University Press.
8. Dong, D. W. & Atick, J. J. (1995a) Temporal decorrelation: a theory of lagged and nonlagged responses in the lateral geniculate nucleus. Network: Computation in Neural Systems, 6, 159-178.
9. Dong, D. W. & Atick, J. J. (1995b) Statistics of natural time-varying images. Network: Computation in Neural Systems, 6, 345-358.
10. Field, D.J. (1987). Relations between the statistics of natural images and the response properties of cortical cells. Journal of the Optical Society of America A, 4, 2379-2394.
11. Field, D. J. (1993). Scale-invariance and self-similar "wavelet" transforms: an analysis of natural scenes and mammalian visual systems. In Farge, M., Hunt, J. C. R. & Vassilicos, J. C. (Eds), Wavelets, fractals, and Fourier transforms (pp. 151-193). Oxford: Clarendon Press.
12. Goldman, S. (1953). Information theory. New York: Dover Publications.
13. van Hateren, J. H. (1992a) Theoretical predictions of spatiotemporal receptive fields of fly LMCs, and experimental validation. Journal of Comparative Physiology A, 171, 157-170.
14. van Hateren, J. H. (1992b) A theory of maximizing sensory information. Biological Cybernetics, 68, 23-29.
15. van Hateren, J. H. (1992c) Real and optimal neural images in early vision. Nature, 360, 68-70.
16. van Hateren, J. H. (1993). Spatiotemporal contrast sensitivity of early vision. Vision Research, 33, 257-267.
17. van Hateren, J. H. & van der Schaaf, A. (1996). Temporal properties of natural scenes. In Proceedings of the IS&T/SPIE Conference on Electronic Imaging: Science and Technology (Vol. 2657, pp. 139-143). San Jose: SPIE.
18. Juusola, M., Uusitalo, R. O. & Weckström, M. (1995). Transfer of graded potentials at the photoreceptor-interneuron synapse. Journal of General Physiology, 105, 117-148.
19. Laughlin, S. B. (1981). A simple coding procedure enhances a neuron's information capacity. Zeitschrift fur Naturforschung, 36c, 910-912.
20. Laughlin, S. B. (1983). Matching coding to scenes to enhance efficiency. In Braddick, O. J. & Sleigh, A. C. (Eds), Physical and biological processing of images (pp. 42-52). New York: Springer.
21. Linsker, R. (1988). Self-organization in a perceptual network. Computer, March 1988, pp. 105-117.
22. Linsker, R. (1993). Deriving receptive fields using an optimal encoding criterion. In Hanson, S. J., Cowan, J. & Giles, C. L. (Eds), Advances in neural information processing systems 5 (pp. 953-960). San Mateo: Morgan Kaufmann.
23. Nadal, J.-P. & Parga, N. (1994). Nonlinear neurons in the low-noise limit: a factorial code maximizes information transfer. Network, 5, 565-581.
24. Richards, W. A. (1982). Lightness scale from image intensity distributions. Applied Optics, 21, 2569-2582.
25. Ruderman, D. L. (1994a) The statistics of natural images. Network: Computation in Neural Systems, 5, 517-548.
26. Ruderman, D. L. (1994b) Designing receptive fields for highest fidelity. Network: Computation in Neural Systems, 5, 147-155.
27. Ruderman, D. L. & Bialek, W. (1994). Statistics of natural images: scaling in the woods. Physics Review Letters, 73, 814-817.
28. de Ruyter van Steveninck, R.R. & Laughlin, S.B. (1996). The rate of information transfer at graded potential synapses. Nature, 379, 642-645.
29. van der Schaaf, A. & van Hateren, J. H. (1996). Modelling the power spectra of natural images: statistics and information. Vision Research, 36, 2759-2770.
30. Shannon, C. E. (1948). The mathematical theory of communication. Bell System Technical Journal, 27, 3-91.
31. Srinivasan, M. V., Laughlin, S. B. & Dubs, A. (1982). Predictive coding: a fresh view of inhibition in the retina. Proceedings of the Royal Society London B, 216, 427-459.
32. Tolhurst, D. J., Tadmor, Y. & Chao, T. (1992). Amplitude spectra of natural images. Ophthalmology and Physiological Optics, 12, 229-232.