Analyzing Neural Responses to Natural Signals: Maximally Informative Dimensions

Neural Computation

Volumn 16, Issue 2, 2004, Pages 223-250

  Sharpee, Tatyana ^a   Rust, Nicole C ^b   Bialek, William ^c  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b NEW YORK UNIVERSITY   (United States)

^c PRINCETON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACTION POTENTIAL; ALGORITHM; ANIMAL; ARTICLE; ARTIFACT; AUDITORY CORTEX; AUDITORY STIMULATION; BIOLOGICAL MODEL; BRAIN; HUMAN; NORMAL DISTRIBUTION; PHOTOSTIMULATION; PHYSIOLOGY; SENSATION; SENSORY NERVE CELL; SIGNAL PROCESSING; VISUAL CORTEX;

ACOUSTIC STIMULATION; ACTION POTENTIALS; ALGORITHMS; ANIMALS; ARTIFACTS; AUDITORY CORTEX; BRAIN; HUMAN; HUMANS; MODELS, NEUROLOGICAL; NEURONS, AFFERENT; NORMAL DISTRIBUTION; PHOTIC STIMULATION; SENSATION; SIGNAL PROCESSING, COMPUTER-ASSISTED; SUPPORT, NON-U.S. GOV'T; SUPPORT, U.S. GOV'T, P.H.S.; VISUAL CORTEX;

EID: 0345768782     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/089976604322742010     Document Type: Article

References (51)

1. Agüera y Arcas, B., Fairhall, A. L., & Bialek, W. (2003). Computation in a single neuron: Hodgkin and Huxley revisited. Neural Comp., 15, 1715-1749.
2. Baddeley, R., Abbott, L. F., Booth, M.C.A., Sengpiel, F., Freeman, T., Wakeman, E. A., & Rolls, E. T. (1997). Responses of neurons in primary and inferior temporal visual cortices to natural scenes. Proc. R. Soc. Lond. B, 264, 1775-1783.
3. Barlow, H. (1961). Possible principles underlying the transformations of sensory images. In W. Rosenblith (Ed.), Sensory communication (pp. 217-234). Cambridge, MA: MIT Press.
4. Barlow, H. (2001). Redundancy reduction revisited. Network: Comput. Neural Syst., 12, 241-253.
5. 6
6. Bialek, W., & de Ruyter van Steveninck, R. R. (2003). Features and dimensions: Motion estimation in fly vision. Unpublished manuscript.
7. Brenner, N., Bialek, W., & de Ruyter van Steveninck, R. R. (2000). Adaptive rescaling maximizes information transmission. Neuron, 26, 695-702.
8. Brenner, N., Strong, S. P., Koberle, R., Bialek, W., & de Ruyter van Steveninck, R. R. (2000). Synergy in a neural code. Neural Computation, 12, 1531-1552. See also physics/9902067.
9. Chichilnisky, E. J. (2001). A simple white noise analysis of neuronal light responses. Network: Comput. Neural Syst, 12, 199-213.
10. Creutzfeldt, O. D., & Northdurft H. C. (1978). Representation of complex visual stimuli in the brain. Naturwissenschaften, 65, 307-318.
11. Cover, T. M., & Thomas, J. A. (1991). Information theory. New York: Wiley.
12. de Boer, E., & Kuyper, P. (1968). Triggered correlation. IEEE Trans. Biomed. Eng., 15, 169-179.
13. de Ruyter van Steveninck, R. R., & Bialek, W. (1988). Real-time performance of a movement-sensitive neuron in the blowfly visual system: Coding and information transfer in short spike sequences. Proc. R. Soc. Land. B, 265, 259-265.
14. de Ruyter van Steveninck, R. R., Borst, A., & Bialek, W. (2000). Real time encoding of motion: Answerable questions and questionable answers from the fly's visual system. In J. M. Zanker, & J. Zeil (Eds.), Motion vision: Computational neural and ecological constraints (pp. 279-306). New York: Springer-Verlag. See also physics/0004060.
15. de Ruyter van Steveninck, R. R., Lewen, G. D., Strong, S. P., Koberle, R., & Bialek, W. (1997). Reproducibility and variability in neural spike trains. Science, 275, 1805-1808. See also cond-mat/9603127.
16. Dimitrov, A. G., & Miller, J. P. (2001). Neural coding and decoding: Communication channels and quantization. Network: Comput. Neural Syst., 12, 441-472.
17. Dong, D. W., & Atick, J. J. (1995). Statistics of natural time-varying images. Network: Comput. Neural Syst., 6, 345-358.
18. Fairhall, A. L., Lewen, G. D., Bialek, W., & de Ruyter van Steveninck, R. R. (2001). Efficiency and ambiguity in an adaptive neural code. Nature, 412, 787-792.
19. Kara, P., Reinagel, P., & Reid, R. C. (2000). Low response variability in simultaneously recorded retinal, thalamic, and cortical neurons. Neuron, 27, 635-646.
20. Lewen, G. D., Bialek, W., & de Ruyter van Steveninck, R. R. (2001). Neural coding of naturalistic motion stimuli. Network: Comput. Neural Syst., 12, 317-329. See also physics/0103088.
21. Mainen, Z. F., & Sejnowski, T. J. (1995). Reliability of spike timing in neocortical neurons. Science, 268, 1503-1506.
22. Paninski, L. (2003a). Convergence properties of three spike-triggered analysis techniques. Network: Compt. in Neural Systems, 14, 437-464.
23. Paninski, L. (2003b). Estimation of entropy and mutual information. Neural Computation, 15, 1191-1253.
24. Panzeri, S., & Treves, A. (1996). Analytical estimates of limited sampling biases in different information measures. Network: Comput. Neural Syst., 7, 87-107.
25. Pola, G., Schultz, S. R., Petersen, R., & Panzeri, S. (2002). A practical guide to information analysis of spike trains. In R. Kotter (Ed.), Neuroscience databases: A practical guide, (pp. 137-152). Norwell, MA: Kluwer.
26. Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. (1992). Numerical recipes in C: The art of scientific computing. Cambridge: Cambridge University Press.
27. Reinagel, P., & Reid, R. C. (2000). Temporal coding of visual information in the thalamus. J. Neurosci., 20, 5392-5400.
28. Rieke, F., Bodnar, D. A., & Bialek, W. (1995). Naturalistic stimuli increase the rate and efficiency of information transmission by primary auditory afferents. Proc. R. Soc. Lond. B, 262, 259-265.
29. Rieke, F., Warland, D., de Ruyter van Steveninck, R. R., & Bialek, W. (1997). Spikes: Exploring the neural code. Cambridge, MA: MIT Press.
30. Ringach, D. L., Hawken, M. J., & Shapley, R. (2002). Receptive field structure of neurons in monkey visual cortex revealed by stimulation with natural image sequences. Journal of Vision, 2, 12-24.
31. Ringach, D. L., Sapiro, G., & Shapley, R. (1997). A subspace reverse-correlation technique for the study of visual neurons. Vision Res., 37, 2455-2464.
32. Rolls, E. T., Aggelopoulos, N. C., & Zheng, F. (2003). The receptive fields of inferior temporal cortex neurons in natural scenes. J. Neurosci., 23, 339-348.
33. Ruderman, D. L. (1994). The statistics of natural images. Network: Compt. Neural Syst., 5, 517-548.
34. Ruderman, D. L., & Bialek, W. (1994). Statistics of natural images: Scaling in the woods. Phys. Rev. Lett., 73, 814-817.
35. Schwartz, O., Chichilnisky, E. J., & Simoncelli, E. (2002). Characterizing neural gain control using spike-triggered covariance. In T. G. Dietterich, S. Becker, & Z. Ghahramani (Eds.), Advances in Neural Information Processing (pp. 269-276). Cambridge, MA: MIT Press.
36. Sen, K., Theunissen, F. E., & Doupe, A. J. (2001). Feature analysis of natural sounds in the songbird auditory forebrain. J. Neurophysiol., 86, 1445-1458.
37. Simoncelli, E., & Olshausen, B. A. (2001). Natural image statistics and neural representation. Annu. Rev. Neurosci., 24, 1193-1216.
38. Smirnakis, S. M., Berry, M. J., Warland, D. K., Bialek, W., & Meister, M. (1996). Adaptation of retinal processing to image contrast and spatial scale. Nature, 386, 69-73.
39. Smyth, D., Willmore, B., Baker, G. E., Thompson, I. D., & Tolhurst, D. J. (2003). The receptive-field organization of simple cells in primary visual cortex of ferrets under natural scene stimulation. J. Neurosci., 23, 4746-4759.
40. Stanley, G. B., Li, F. F., & Dan, Y. (1999). Reconstruction of natural scenes from ensemble responses in the lateral geniculate nucleus. J. Neurosci., 19, 8036-8042.
41. Strong, S. P., Koberle, R., de Ruyter van Steveninck, R. R., & Bialek, W. (1998). Entropy and information in neural spike trains. Phys. Rev. Lett., 80, 197-200.
42. Theunissen, F. E., Sen, K., & Doupe, A. J. (2000). Spectral-temporal receptive fields of nonlinear auditory neurons obtained using natural sounds. J. Neurosci., 20, 2315-2331.
43. Tishby, N., Pereira, F. C., & Bialek, W. (1999). The information bottleneck method. In B. Hajek & R. S. Sreenivas (Eds.), Proceedings of the 37th Allerton Conference on Communication, Control and Computing (pp. 368-377). Urbana: University of Illinois. See also physics/0004057.
44. Touryan J., Lau, B., & Dan, Y. (2002). Isolation of relevant visual features from random stimuli for cortical complex cells. J. Neurosci., 22, 10811-10818.
45. Treves, A., & Panzeri, S. (1995). The upward bias in measures of information derived from limited data samples. Neural Comp., 7, 399-407.
46. von der Twer, T., & Macleod, D. I. A. (2001). Optimal nonlinear codes for the perception of natural colours. Network: Comput. Neural Syst., 12, 395-407.
47. Vickers, N. J., Christensen, T. A., Baker, T., & Hildebrand, J. G. (2001). Odourplume dynamics influence the brain's olfactory code. Nature, 410, 466-470.
48. Vinje, W. E., & Gallant, J. L. (2000). Sparse coding and decorrelation in primary visual cortex during natural vision. Science, 287, 1273-1276.
49. Vinje, W. E., & Gallant, J. L. (2002). Natural stimulation of the nonclassical receptive field increases information transmission efficiency in V1. J. Neurosci., 22, 2904-2915.
50. Voss, R. F., & Clarke, J. (1975). "1/f noise" in music and speech. Nature, 317-318.
51. Weliky, M., Fiser, J., Hunt, R., & Wagner, D. N. (2003). Coding of natural scenes in primary visual cortex. Neuron, 37, 703-718.