Topographic independent component analysis

Neural Computation

Volumn 13, Issue 7, 2001, Pages 1527-1558

  Hyvärinen, Aapo ^a   Hoyer, Patrik O ^a   Inki, Mika ^a  

^a AALTO UNIVERSITY   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ANALYSIS OF VARIANCE; ARTICLE; ARTIFACT; BIOLOGICAL MODEL; BLINKING; BRAIN MAPPING; HUMAN; MAGNETOENCEPHALOGRAPHY; MASTICATION; METHODOLOGY; MUSCLE CONTRACTION;

ALGORITHMS; ANALYSIS OF VARIANCE; ARTIFACTS; BLINKING; BRAIN MAPPING; HUMANS; MAGNETOENCEPHALOGRAPHY; MASTICATION; MODELS, NEUROLOGICAL; MUSCLE CONTRACTION;

EID: 0035409349     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/089976601750264992     Document Type: Article

References (44)

1. Amari, S.-I., Cichocki, A., & Yang, H. (1996). A new learning algorithm for blind source separation. In D. Touretzky, M. Mozer, & M. Hasselmo (Eds.), Advances in neural information processing systems 8 (pp. 757-763). Cambridge, MA: MIT Press.
2. Bell, A., & Sejnowski, T. (1995). An information-maximization approach to blind separation and blind deconvolution. Neural Computation, 7, 1129-1159.
3. Bell, A., & Sejnowski, T. (1997). The "independent components" of natural scenes are edge filters. Vision Research, 37, 3327-3338.
4. Bishop, C. M., Svensen, M., & Williams, C. K. I. (1998). GTM: The generative topographic mapping. Neural Computation, 10, 215-234.
5. Blasdel, G. G. (1992). Orientation selectivity, preference, and continuity in monkey striate cortex. Journal of Neuroscience, 12(8), 3139-3161.
6. Blasdel, G., & Obermayer, K. (1994). Putative strategies of scene segmentation in monkey visual cortex. Neural Networks, 7, 865-881.
7. Cardoso, J.-F. (1998). Multidimensional independent component analysis. In Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP'98). Seattle, WA.
8. Cardoso, J.-F., & Laheld, B. H. (1996). Equivariant adaptive source separation. IEEE Transactions on Signal Processing, 44(12), 3017-3030.
9. Cichocki, A., & Unbehauen, R. (1996). Robust neural networks with on-line learning for blind identification and blind separation of sources. IEEE Transactions on Circuits and Systems, 43(11), 894-906.
10. Comon, P. (1994). Independent component analysis - a new concept? Signal Processing, 36, 287-314.
11. DeAngelis, G. C., Ghose, G. M., Ohzawa, I., & Freeman, R. D. (1999). Functional micro-organization of primary visual cortex: Receptive field analysis of nearby neurons. Journal of Neuroscience, 19(10), 4046-4064.
12. Delfosse, N., & Loubaton, P. (1995). Adaptive blind separation of independent sources: A deflation approach. Signal Processing, 45, 59-83.
13. Dempster, A. P., Laird, N., & Rubin, D. (1977). Maximum likelihood for incomplete data via the EM algorithm. Journal of the Royal Statistical Society, ser. B, 39, 1-38.
14. Durbin, R., & Mitchison, G. (1990). A dimension reduction framework for understanding cortical maps. Nature, 343, 644-647.
15. Emerson, R. C., Bergen, J. R., & Adelson, E. H. (1992). Directionally selective complex cells and the computation of motion energy in cat visual cortex. Vision Research, 32, 203-218.
16. Goodhill, G. J., & Sejnowski, T. J. (1997). A unifying objective function for topographic mappings. Neural Computation, 9(6), 1291-1303.
17. Graepel, T., & Obermayer, K. (1999). A stochastic self-organizing map for proximity data. Neural Computation, 11, 139-155.
18. Gray, M. S., Pouget, A., Zemel, R. S., Nowlan, S. J., & Sejnowski, T. J. (1998). Reliable disparity estimation through selective integration. Visual Neuroscience, 15(3), 511-528.
19. Heeger, D. (1992). Normalization of cell responses in cat striate cortex. Visual Neuroscience, 9, 181-198.
20. Hyvärinen, A. (1998). New approximations of differential entropy for independent component analysis and projection pursuit. In M. Kearns, M. Jordan, & S. Solla (Eds.), Advances in neural information processing systems, 10 (pp. 273-279). Cambdrige, MA: MIT Press.
21. Hyvärinen, A. (1999a). Fast and robust fixed-point algorithms for independent component analysis. IEEE Transactions on Neural Networks, 10(3), 626-634.
22. Hyvärinen, A. (1999b). Sparse code shrinkage: Denoising of nongaussian data by maximum likelihood estimation. Neural Computation, 11(7), 1739-1768.
23. Hyvärinen, A. (1999c). Survey on independent component analysis. Neural Computing Surveys, 2, 94-128.
24. Hyvärinen, A., & Hoyer, P. O. (2000). Emergence of phase and shift invariant features by decomposition of natural images into independent feature subspaces. Neural Computation, 12(7), 1705-1720.
25. Hyvärinen, A., & Oja, E. (1997). A fast fixed-point algorithm for independent component analysis. Neural Computation, 9(7), 1483-1492.
26. Hyvärinen, A., Särelä, J., & Vigário, R. (1999). Spikes and bumps: Artifacts generated by independent component analysis with insufficient sample size. In Proc. Int. Workshop on Independent Component Analysis and Signal Separation (ICA'99) (pp. 425-429). Aussois, France.
27. Jutten, C., & Hérault, J. (1991). Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture. Signal Processing, 24, 1-10.
28. Karhunen, J., Oja, E., Wang, L., Vigário, R., & Joutsensalo, J. (1997). A class of neural networks for independent component analysis. IEEE Transactions on Neural Networks, 8(3), 486-504.
29. Kiviluoto, K., & Oja, E. (1998). S-Map: A network with a simple self-organization algorithm for generative topographic mappings. In M. Kearns, M. Jordan, & S. Solla (Eds.), Advances in neural information processing systems, 10. Cambridge, MA: MIT Press.
30. Kohonen, T. (1995). Self-organizing maps. New York: Springer-Verlag.
31. Kohonen, T. (1996). Emergence of invariant-feature detectors in the adaptive-subspace self-organizing map. Biological Cybernetics, 75, 281-291.
32. Lin, J. K. (1998). Factorizing multivariate function classes. In M. Kearns, M. Jordan, & S. Solla (Eds.), Advances in neural information processing systems, 10 (pp. 563-569). Cambridge, MA: MIT Press.
33. Mel, B. W., Ruderman, D. L., & Archie, K. A. (1998). Translation-invariant orientation tuning in visual "complex" cells could derive from intradendritic computations. Journal of Neuroscience, 18, 4325-4334.
34. Nelson, M. E., & Bower, J. M. (1990). Brain maps and parallel computers. Trends in Neurosciences, 13(10), 403-408.
35. Oja, E. (1997). The nonlinear PCA learning rule in independent component analysis. Neurocomputing, 17(1), 25-46.
36. Olshausen, B. A., & Field, D. J. (1996). Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature, 381, 607-609.
37. Olshausen, B. A., & Field, D. J. (1997). Sparse coding with an overcomplete basis set: A strategy employed by V1? Vision Research, 37, 3311-3325.
38. Pajunen, P. (1998). Blind source separation using algorithmic information theory. Neurocomputing, 22, 35-48.
39. Pham, D.-T., Garrat, P., & Jutten, C. (1992). Separation of a mixture of independent sources through a maximum likelihood approach. In Proc. EUSIPCO (pp. 771-774).
40. Simoncelli, E. P., & Schwartz, O. (1999). Modeling surround suppression in V1 neurons with a statistically-derived normalization model. In M. Kearns, S. Solla, & D. Cohn (Eds.), Advances in neural information processing systems, 11 (pp. 153-159). Cambridge, MA: MIT Press.
41. Swindale, N. V. (1996). The development of topography in the visual cortex: A review of models. Network, 7(2), 161-247.
42. van Hateren, J. H., & van der Schaaf, A. (1998). Independent component filters of natural images compared with simple cells in primary visual cortex. Proceedings of the Royal Society ser. B, 265, 359-366.
43. Vigário, R. (1997). Extraction of ocular artifacts from EEG using independent component analysis. Electroenceph. Clin. Neurophysiol., 103(3), 395-404.
44. Vigário, R., Jousmäki, V., Hämäläinen, M., Hari, R., & Oja, E. (1998). Independent component analysis for identification of artifacts in magnetoencephalographic recordings. In In M. Kearns, M. Jordan, & S. Solla (Eds.), Advances in neural information processing systems, 10 (pp. 229-235). Cambridge, MA: MIT Press.