Creating hierarchical categories using cell assemblies

Connection Science

Volumn 19, Issue 1, 2007, Pages 1-24

  Huyck, Christian R ^a  

^a MIDDLESEX UNIVERSITY   (United Kingdom)

Author keywords

Attractor net; Cell assembly; Hebbian learning; Hierarchical categorization

Indexed keywords

ATTRACTOR NET; CELL ASSEMBLY; DEFAULT INFORMATION; HEBBIAN LEARNING; HIERARCHICAL CATEGORIZATION; LEARNING RULES;

RECURRENT NEURAL NETWORKS;

COMPUTER SIMULATION;

EID: 33947405269     PISSN: 09540091     EISSN: 13600494     Source Type: Journal    
DOI: 10.1080/09540090600779713     Document Type: Article

References (84)

1. Abeles, H. Bergman, E. Margalit, and E. Vaadia, "Spatiotemporal firing patterns in the frontal cortex of behaving monkeys", J. Neurophysiol., 70, pp. 1629-1638, 1993.
2. Ackley, G. Hinton, and T. Sejnowski, "A learning algorithm for Boltzmann machines", Cognitive Sci., 9, pp. 147-169, 1985.
3. Amit, Modelling Brain Function: The World of Attractor Neural Networks, Cambridge: Cambridge University Press, 1989.
4. Amit and N. Brunel, "Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex", Cerebral Cortex, 7, pp. 237-252, 1997.
5. Amit and G. Mongillo, "Spike-driven synaptic dynamics generating working memory states", Neural Computat., 15, pp. 565-596, 2003.
6. G. Athithan, "Associative memory of low activity patterns with the problem of spurious attractors", Current Sci., 76, pp. 540-547, 1999.
7. H. Barlow, "Single units and sensation: a neuron doctorine for perceptual psychology?" Perception, 1, pp. 371-394, 1972.
8. Bevan and C. Wilson, "Mechanisms underlying spontaneous oscillation and rhythmic firing in rat subthalamic neurons", J. Neurosci., 19, pp. 7617-28, 1999.
9. Blake and C. Merz, UCI repository of machine learning databases [http://www.ics.uci.edu/mlearn/mlrepository.html], Irvine, CA: University of California, Department of Information and Computer Science, 1998.
10. J. Bower and D. Beeman, The Book of GENESIS, Berlin: Springer-Verlag, 1995.
11. Bratenberg, "Some arguments for a theory of cell assemblies in the cerebral cortex", in Neural Connections, Mental Computation. L. Nadel, Ed, Cambridge, MA: MIT Press, 1989.
12. N. Brunel, "Hebbian learning of context in recurrent neural networks", Neural Computat., 8, pp. 1677-1710, 1996.
13. W. Calvin, "Cortical columns, modules, and Hebbian cell assemblies", in The Handbook of Brain Theory and Neural Networks, M. Arbib, Ed., Cambridge, MA: MIT Press, 1995.
14. Cardie, "Using cognitive biases to guide feature set selection", in Proceedings of the 14th Annual Conference of the Cognitive Science Society, 1992, pp. 743-748.
15. E. Chown, "Making predictions in an uncertain world: environmental structure and cognitive maps", Adapt. Behav., 7, pp. 1-17, 1999.
16. Churchland P.S. Churchland and T.J. Sejnowski, The Computational Brain, Cambridge, MA: MIT Press, 1992.
17. A. Collins and E. Loftus, "A spreading-activation theory of semantic processing", Psychol. Rev., 82, pp. 407-428, 1975.
18. Connolly and R. Reilly, "A proposed model of repetition blindness", in Modelling Language, Cognition and Action: Proceedings of the 9th Neural Compuation and Psychology Workshop, A. Cangelosi, G. Bugmann, R. Borisyuk, Eds, Singapore: World Scientific, 2005, pp. 279-288.
19. G. Dalenoort, "The representation of tasks in active cognitive networks", Cognitive Syst., 1, pp. 253-272, 1985.
20. J. Eccles, "Chemical transmission and Dale's principle", Prog. Brain Res., 68, pp. 3-13, 1986.
21. J. Elman, "Finding structure in time", Cognitive Sci., 14, pp. 179-211, 1990.
22. Erickson and J. Kruschke, "Rules and exemplars in category learning", J. Exp. Psychol.: Gen., 127, pp. 107-140, 1998.
23. Feigelman and L. Ioffe, "The augmented models of associative memory asymmetric interaction and hierarchy of patterns", J. Mod. Phys. B, 1, pp. 51-68, 1987.
24. J. Fodor, The Mind Doesn't Work That Way: the Scope and Limits of Computational Psychology, Cambridge, MA: MIT Press, 2000.
25. E. Fransen, A. Lanser, and H. Liljenstrom, "A model of cortical associative memory based on Hebbian cell assemblies", in Connectionism in a Broad Perspective, L. Niklasson, M. Boden, Eds, Berlin: Ellis Horwood Springer-Verlag, 1992, pp. 165-171.
26. W. Freeman, "Mesoscopic neurodynamics: from neuron to brain", J. Physiol., 94, pp. 303-322, 2000.
27. L.L. Fu, "An analysis of Hebb's cell assembly as a mechanism for perceptual generalisation". PhD thesis, University of Michigan, Ann Arbor (2003).
28. W. Gerstner, "Time structure of the activity in neural network models", Phys. Rev. E, 51, pp. 738-758, 1995.
29. S. Grossberg, "Competitive learning: from interactive activation to adaptive resonance", Cognitive Sci., 11, pp. 23-63, 1987.
30. S. Hanson and M. Bauer, "Conceptual clustering, categorization, and polymorphy", Machine Learning, 3, pp. 343-372, 1989.
31. S. Hanson and M. Negishi, "On the emergence of rules in neural networks", Neural Computat., 14, pp. 245-268, 2002.
32. D.O. Hebb, The Organization of Behavior, New York: J. Wiley & Sons, 1949.
33. J. Hertz, A. Krogh, and R. Palmer, Introduction to the Theory of Neural Computation, Cambridge, MA: Perseus Books, 1991.
34. P. Hetherington and M. Shapiro, "Simulating Hebb cell assemblies: the necessity for partitioned dendritic trees and a post-net-pre LTD rule", Network: Computat. Neural Syst., 4, pp. 135-153, 1993.
35. Hindle and M. Rooth, "Structural ambiguity and lexical relations", Computat. Linguist., 19, pp. 103-120, 1993.
36. G. Hinton and T. Sejnowski, "Optimal perceptual inference", in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1983, pp. 448-453.
37. A. Hodgkin and A. Huxley, "A quantitative description of membrane current and its application to conduction and excitation in nerve", J. Physiol., 117, pp. 500-544, 1952.
38. J. Hopfield, "Neural nets and physical systems with emergent collective computational abilities", Proc. Nat. Acad. Sci. USA, 79, pp. 2554-2558, 1982.
39. Horn, N. Levy, and E. Ruppin, "Memory maintenance via neuronal regulation", Neural Computat., 10, pp. 1-18, 1998.
40. Horn, E. Ruppin, M. Usher, and M. Herrmann, "Neural network modeling of memory deterioration in Alzheimer's disease", Neural Computat., 5, pp. 736-749, 1993.
41. Horn and M. Usher, "Neural networks with dynamical thresholds", Am. Phys. Rev., 40, pp. 1036-1044, 1989.
42. Huyck, "Cell assemblies for rapid recognition and disambiguation", in EmerNet: Third International Workshop on Current Computational Architectures Integrating Neural Networks and Neuroscience, 2000.
43. Huyck, "Cell assemblies and neural network theory: from correlators to cell assemblies", Technical report, London: Middlesex University, 2002.
44. Huyck, "Overlapping cell assemblies from correlators", Neurocomputing, 56, pp. 435-439, 2004.
45. Huyck, "Variable binding of cell assemblies with binding areas and spontaneous neural activation", in Proceedings of the Twenty Second Workshop of the European Society for the Study of Cognitive Systems, 2005.
46. C.R. Huyck, "Cell assemblies as an intermediate level model of cognition", in Emerging Neural Architectures Based on Neuroscience, S. Wermter, J. Austin, D. Willshaw, Eds, Berlin: Springer, 2001.
47. Huyck-Belavkin C. Huyck and R. Belavkin, "Counting with neurons: rule application with nets of fatiguing leaky integrate and fire neurons", in Proceedings of the Seventh International Conference on Cognitive Modelling, 2006.
48. Huyck and R. Bowles, "Spontaneous neural firing in biological and artificial neural systems", J. Cognitive Syst., 6, pp. 31-40, 2004.
49. Huyck and H. Ghalib, "Improving cell assembly categories by fatigue", in Proceedings of the Ninth Neural Computation and Psychology Workshop, 2004.
50. Huyck and I. Mitchell, "Cell assemblies, self-organising maps and Hopfield networks", in Proceedings of the Sixth International Conference on Cognitive and Neural Systems, 2002.
51. Huyck and V. Orengo, "Information retrieval and categorisation using a cell assembly network", Neural Comput. Appl., 14, pp. 282-289, 2005.
52. A. Jahnke, U. Roth, and H. Klar, "Towards efficient hardware for spike-processing neural networks", in Proceedings of the World Congress on Neural Networks, 1995, pp. 460-463.
53. W. James, Psychology: The Briefer Course, Notre Dame, Indiana: University of Notre Dame Press, 1892.
54. S. Kaplan, M. Sontag, and E. Chown, "Tracing recurrent activity in cognitive elements (trace): a model of temporal dynamics in a cell assembly", Connect. Sci., 3, pp. 179-206, 1991.
55. Kieras, S. Wood, and D. Meyer, "Predictive engineering models based on the epic architecture for a multimodal high-performance human-computer interaction task", ACM Trans. Comput. Human Interact., 4, pp. 230-75, 1997.
56. A. Knoblauch, H. Markert, and G. Palm, "An associative model of cortical langauage and action processing", in Proceedings of the Ninth Neural Computation and Psychology Workshop, 2004.
57. A. Knoblauch and G. Palm, "Pattern separation and synchronization in spiking associative memories and visual areas", Neural Networks, 14, pp. 763-780, 2001.
58. T. Kohenen, Self-Organizing Maps, Berlin: Springer, 1997.
59. S. Levy, O. Melnik, and J. Pollack, "Infinite RAAM: a principled connectionist basis for grammatical competence", in Proceedings of the 20th Annual Conference of the Cognitive Science Society, 2000.
60. R. Lippmann, "An introduction to computing with neural nets", IEEE ASSP Mag., 4, pp. 4-22, 1987.
61. W. Maas and C. Bishop, Pulsed Neural Networks, Cambridge, MA: MIT Press, 2001.
62. A. Newell, Unified Theories of Cognition, Cambridge, MA: Harvard University Press, 1990.
63. E. Oja, "A simplified neuron model as a principal component analyzer", J. Math. Biol., 15, pp. 267-273, 1982.
64. G. Palm, "Cell assemblies as a guideline for brain research", Concepts Neurosci., 1, pp. 133-147, 1990.
65. J. Pollack, "Recursive distributed representations", Artif. Intell., 46, pp. 77-105, 1990.
66. F. Pulvermuller, "Words in the brain's language", Behav. Brain Sci., 22, pp. 253-336, 1999.
67. Quillian, "Word concepts: a theory of simulation of some basic semantic capabilities", Behav. Sci., 12, pp. 410-430, 1967.
68. Riesenhuber M. Riesenhuber and T. Poggio, How Visual Cortex Recognizes Objects: The Tale of the Standard Model, Cambridge, MA: MIT Press, 2003.
69. N. Rochester, J. Holland, L. Haibt, and W. Duda, "Tests on a cell assembly theory of the action of the brain using a large digital computer", RE Trans. Informat. Theory, IT-2, pp. 80-93, 1956.
70. E. Rosch and C. Mervis, "Family resemblances: studies in the internal structure of categories", Cognitive Psychol., 1, pp. 573-605, 1975.
71. Y. Roudi and A. Treves, "An associative network with spatially organized connectivity", J. Stat. Mech.: Theory Exp., 7, pp. 7-32, 2004.
72. Rumelhart and J. McClelland, "An interactive activation model of context effects in letter perception: Part 2. the contextual enhancement and some tests and extensions of the model", Psychol. Rev., 89, pp. 60-94, 1982.
73. Rumelhart and J. McClelland, Parallel Distributed Processing, Cambridge, MA: MIT Press, 1986.
74. Y. Sakurai, "The search for cell assemblies in the working brain", Behav. Brain Res., 91, pp. 1-13, 1998.
75. T. Sanger, "Optimal unsupervised learning in a single-layer linear feedforward neural network", Neural Networks, 2, pp. 459-473, 1989.
76. R. Shepard, C. Hovland, and H. Jenkins, "Learninng and memorization of classifications", Psychol. Monographs, 75, p. 517, 1961.
77. J. Sougne, "Binding and multiple instantiation in a distributed network of spiking neurons", Connect. Sci., 13, pp. 99-126, 2001.
78. Stevens and A. Zador, "Novel integrate-and-fire-like model of repetitive firing in cortical neurons", in Proceedings of the Fifth Symposium on Neural Computation, 1998.
79. R. Sun, "Robust reasoning: integrating rule-based and similarity based reasoning", Artif. Intell., 75, pp. 241-95, 1995.
80. Tal and E. Schwartz, "Computing with the leaky integrate-and-fire neuron: logarithmic computation and multiplication", Neural Computat., 9, pp. 305-318, 1997.
81. Tsodyks, K. Pawelzik, and H. Markram, "Neural networks with dynamic synapses", Neural Computat., 10, pp. 821-35, 1998.
82. A. Turing, "Computing machinery & intelligence", Mind, 59, pp. 433-460, 1950.
83. W. Wickelgren, "Webs, cell assemblies, and chunking in neural nets", Canad. J. Exp. Psychol., 53, pp. 118-131, 1999.
84. L. Wittgenstein, Philosphical Investigations, Oxford: Blackwell, 1953.