Marr's theory of the neocortex as a self-organizing neural network

Neural Computation

Volumn 9, Issue 4, 1997, Pages 911-936

  Willshaw, David ^a   Hallam, John ^a   Gingell, Sarah ^a   Lau, Soo Leng ^a  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; BRAIN CORTEX; DEPTH PERCEPTION; HUMAN; NERVE FIBER; PHYSIOLOGY; PYRAMIDAL NERVE CELL; SYNAPSE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CEREBRAL CORTEX; HUMANS; NERVE FIBERS; NEURAL NETWORKS (COMPUTER); PYRAMIDAL CELLS; SPACE PERCEPTION; SYNAPSES;

EID: 0031570015     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/neco.1997.9.4.911     Document Type: Article

References (36)

1. Bennett, M. R., & Robinson, J. (1989). Growth and elimination of nerve terminals at synaptic sites during polyneuronal innervation of muscle cells: A trophic hypothesis. Proceedings of the Royal Society of London B, 235, 299-320.
2. Bienenstock, E., Cooper, L., & Munro, P. (1982). Theory for the development of neuron selectivity: Orientation specificity and binocular interaction in visual cortex. Journal of Neuroscience, 2, 32-48.
3. Bishop, C. M. (1995). Neural networks for pattern recognition. New York: Oxford University Press.
4. Cohen, M. A., & Grossberg, S. (1983). Absolute stability of global pattern formation and parallel memory storage by competitive neural networks. IEEE Transactions on Systems, Man and Cybernetics, 13, 815-826.
5. Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society B, 39, 1-38.
6. Durbin, R., & Willshaw, D. (1987). An analogue approach to the travelling salesman problem using an elastic net method. Nature, 326, 689-691.
7. Gingell, S. (1994). Extension of Lau's 1992 simulation of Marr's theory of the neocortex. Unpublished master's thesis, University of Edinburgh.
8. Goodhill, G. J., & Barrow, H. G. (1994). The role of weight normalization in competitive learning. Neural Computation, 6, 255-269.
9. Goodhill, G. J., & Willshaw, D. J. (1990). Application of the elastic net algorithm to the formation of ocular dominance stripes. Network, 1, 41-59.
10. Gouzé, J. L., Lasry, J. M., & Changeux, J. P. (1983). Selective stabilization of muscle innervation during development: A mathematical model. Biological Cybernetics, 46, 207-215.
11. Grossberg, S. (1976). Adaptive pattern classification and universal recoding: I. Parallel development and coding of neural feature detectors. Biological Cybernetics, 23, 121-134.
12. Hebb, D. (1949). The organization of behavior. New York: Wiley.
13. Kingman, J. F. C., & Taylor, S. J. (1966). Introduction to measure and probability. Cambridge: Cambridge University Press.
14. Kohonen, T. (1982). Self-organized formation of topologically correct feature maps. Biological Cybernetics, 43, 59-69.
15. Lau, S. L. (1992). Analysis of Marr's model of the neocortex. Unpublished master's thesis, University of Edinburgh.
16. Ljung, L. (1975). Theorems for the asymptotic analysis of recursive stochastic algorithms (Tech. Rep. No. 7522). Lund, Sweden: Lund Institute of Technology.
17. Marr, D. (1969). A theory of cerebellar cortex. Journal of Physiology (London), 202, 437-470.
18. Marr, D. (1970). A theory for cerebral neocortex. Proceedings of the Royal Society of London B, 176, 161-234.
19. Marr, D. (1971). Simple memory: A theory for archicortex. Philosophical Transactions of the Royal Society of London B, 262, 23-81.
20. Miller, K. D., Keller, J. B., & Stryker, M. P. (1989). Ocular dominance column development: Analysis and simulation. Science, 245, 605-615.
21. Miller, K. D., & MacKay, D. J. C. (1994). The role of constraints in Hebbian learning. Neural Computation, 6, 100-126.
22. Minsky, M., & Papert, S. (1969). Perceptrons. Cambridge, MA: MIT Press.
23. Moody, J., & Darken, C. (1989). Fast learning in networks of locally-tuned processing units. Neural Computation, 1, 281-294.
24. Prestige, M. C., & Willshaw, D. J. (1975). On a role for competition in the formation of patterned neural connexions. Proceedings of the Royal Society of London B, 190, 77-98.
25. Rasmussen, C. E., & Willshaw, D. J. (1993). Presynaptic and postsynaptic competition in models for the development of neuromuscular connections. Biological Cybernetics, 68, 409-419.
26. Rumelhart, D., & Zipser, D. (1985). Feature discovery by competitive learning. Cognitive Science, 9, 75-112.
27. Sibson, R. (1969). Information radius. Wahrscheinlichkeitstheorie, 14, 149-160.
28. Swindale, N. V. (1980). A model for the formation of ocular dominance stripes. Proceedings of the Royal Society of London B, 208, 243-264.
29. von der Malsburg, C. (1973). Self-organization of orientation sensitive cells in the striate cortex. Kybernetik, 14, 85-100.
30. von der Malsburg, C, & Willshaw, D. J. (1981). Differential equations for the development of topological nerve fibre projections. SIAM-AMS Proceedings, 13, 39-47.
31. Widrow, B., & Hoff, M. (1960). Adaptive switching circuits. In 1960 IREWESCON Convention Record (Vol. 4, pp. 96-104). New York: IRE.
32. Willshaw, D. J. (1972). A simple network capable of inductive generalisation. Proceedings of the Royal Society of London B, 182, 233-247.
33. Willshaw, D. J. (1981). The establishment and the subsequent elimination of polyneural innervation of developing muscle: theoretical considerations. Proceedings of the Royal Society of London B, 212, 233-252.
34. Willshaw, D. J., & Buckingham, J. T. (1990). An assessment of Marr's theory of the hippocampus as a temporary memory store. Proceedings of the Royal Society of London B, 329, 205-215.
35. Willshaw, D. J., & von der Malsburg, C. (1976). How patterned neural connections can be set up by self-organization. Proceedings of the Royal Society of London B, 194, 431-445.
36. Willshaw, D. J., & von der Malsburg, C. (1979). A marker induction mechanism for the establishment of ordered neural mappings: Its application to the retinotectal problem. Philosophical Transactions of the Royal Society of London B, 287, 203-243.