Finding independent components using spikes: A natural result of hebbian learning in a sparse spike coding scheme

Natural Computing

Volumn 3, Issue 2, 2004, Pages 159-175

  Perrinet, Laurent ^a  

^a Institut de neurosciences cognitives de la Méditerranée   (France)

Author keywords

Emergence; Hebbian learning; Natural images statistics; Over complete representation; Parallel asynchronous processing; Sparse spike coding; Vision; Wavelet transform

Indexed keywords

ALGORITHM; ARTICLE; CENTRAL NERVOUS SYSTEM; CONTROLLED STUDY; IMAGE PROCESSING; INFORMATION PROCESSING; LUMINANCE; MATHEMATICAL COMPUTING; NERVE CELL EXCITABILITY; NERVE CELL STIMULATION; NEUROPHYSIOLOGY; PHOTORECEPTOR; RETINA IMAGE; RETINA RECEPTIVE FIELD; VISION; VISUAL CORTEX;

EID: 4344683592     PISSN: 15677818     EISSN: None     Source Type: Journal    
DOI: 10.1023/B:NACO.0000027753.27593.a7     Document Type: Article

References (32)

1. Adrian E (1928) The Basis of Sensation: The Action of Sense Organs. Christophers, London
2. Bell AJ and Sejnowski TJ (1997) The 'independent components' of natural scenes are edge filters. Vision Research 37(23): 3327-3338
3. Celebrini S, Thorpe SJ, Trotter Y and Imbert M (1993) Dynamics of orientation coding in area V1 of the awake primate. Vis Neurosci 5(10): 811-825
4. Chance F, Nelson SB and Abbott LF (1998) Synaptic depression and the temporal response characeristics of V1 simple cells. The Journal of Neuroscience 18: 4785-4799
5. Comon P (1994) Independent Component analysis, a new concept? Signal Processing 36(3): 287-314
6. Daugman J and Downing C (1995) Gabor Wavelets for Statistical Pattern Recognition, pp. 414-419. The MIT Press, Cambridge, MA
7. Field DJ (1994) What is the goal of sensory coding? Neural Computation 6(4): 559-601
8. Linsker R (1986) From basic network principles to neural architecture: emergence of spacial-opponent cells/orientation-selective cells/orientation columns. Proceedings of the National Academy of Sciences 83: 7508-7512, 8390-8394, 8779-8783
9. Mallat S (1998) A Wavelet Tour of Signal Processing. Academic Press
10. Mallat S and Zhang Z (1993) Matching pursuit with time-frequency dictionaries. IEEE Transactions on Signal Processing 41(12): 3397-3414
11. Mallat S and Zhong S (1992) Wavelet transform maxima and multiscale edge
12. Marr D (1982) Vision. W.H. Freeman and Company, NY
13. Oja E (1982) A simplified neuron model as a principal component analyzer. J. Math. Biol. (15): 267-273
14. Olshausen B and Field DJ (1996) Natural image statistics and efficient coding. Network 7: 333-339
15. Olshausen B and Field DJ (1998) Sparse coding with an overcomplete basis set: a strategy employed by V1? Vision Research 37: 3311-3325
16. Olshausen B, Sallee P and Lewicki MS (1998) Learning sparse wavelet codes for natural images. In: Jordan MI, Kearns MJ and Solla SA (eds) Advances in Neural Information Processing Systems, Vol. 12. The MIT Press, Cambridge, MA
17. Perrinet L and Samuelides M (2002a) Coherence detection in a spiking neuron via Hebbian learning. Neurocomputing 44-46(C): 133-139
18. Perrinet L and Samuelides M (2002b) Sparse image coding using an asynchronous spiking neural network. In: Proceedings of ESANN, pp. 313-318
19. Perrinet L, Samuelides M and Thorpe S (2002) Sparse spike coding in an asynchronous feed-forward multi-layer neural network using Matching Pursuit. Neurocomputing, in press
20. Perrinet L, Samuelides M and Thorpe S (2003) Coding static natural images using spiking event times: do neurons cooperate?. Submitted
21. Rodieck RW (1965) Quantitative analysis of cat retinal ganglion cell response to visual stimuli. Vision Research 5: 583-601
22. Salinas E and Abbott L (2000) Do simple cells in primary visual cortex form a tight frame. Neural Computation 12(2): 313-335
23. Schwartz O and Simoncelli E (2001) Natural signal statistics and sensory gain control. Nature Neuroscience 4(8): 819-825
24. Thorpe SJ, Delorme A, Van Rullen R and Paquier W (2000) Reverse engineering of the visual system using networks of spiking neurons. In: IEEE International Symposium on Circuits and Systems, Vol. 4, pp. 405-408
25. Thorpe SJ and Fabre-Thorpe M (2001) Neuroscience. Seeking categories in the brain. Science 291(5502): 260-263 Comment on: Science, 2001 Jan 12; 291(5502): 312-316
26. Thorpe SJ, Fize D and Marlot C (1996) Speed of processing in the human visual system. Nature 381: 520-522
27. Thorpe SJ and Gautrais J (1998) Rank order coding. In: Bower J (ed) Computational Neuroscience: Trends in Research 1998, pp. 113-118. Plenum Press, New York
28. van Hateren J and van der Schaaf A (1998) Independent component filters of natural images compared with simple cells in primary visual cortex. Proc. R. Soc. Lond. B 265: 359-366
29. Van Rullen R and Thorpe SJ (2001) Rate coding versus temporal order coding: what the retina ganglion cells tell the visual cortex. Neural Computation 13(6): 1255-1283
30. Vapnik V (1995) The Nature of Statistical Learning Theory. Springer, New York
31. Vinje WE and Gallant JL (2000) Sparse coding and decorrelation in primary visual cortex during natural vision. Science 287: 1273-1276
32. Zibulevsky M and Pearlmutter BA (2001) Blind source separation by sparse decomposition in a signal dictionary. Neural Computation 13(4): 863-882