Network capacity analysis for latent attractor computation

Network: Computation in Neural Systems

Volumn 14, Issue 2, 2003, Pages 273-302

  Doboli, Simona ^a   Minai, Ali A ^b  

^a HOFSTRA UNIVERSITY   (United States)

^b 705 Engineering Research Center   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACTION POTENTIAL; ANALYTIC METHOD; ANIMAL; ARTICLE; ARTIFICIAL NEURAL NETWORK; ASSOCIATIVE MEMORY; BRAIN MAPPING; CELLULAR DISTRIBUTION; CORRELATION ANALYSIS; CYTOLOGY; DENDRITE; DENDRITIC CELL; DEPTH PERCEPTION; HIPPOCAMPUS; LEARNING; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; MEMORY; NERVE CELL; NERVE CELL NETWORK; NONHUMAN; NORMAL DISTRIBUTION; PHYSIOLOGY; PYRAMIDAL NERVE CELL; QUANTITATIVE ANALYSIS; RAT; SIGNAL NOISE RATIO; THEORETICAL MODEL;

ANIMALS; ASSOCIATION LEARNING; BRAIN MAPPING; CYTOLOGY; DENDRITES; HIPPOCAMPUS; MEMORY; NEURAL NETWORKS (COMPUTER); PHYSIOLOGY; SPACE PERCEPTION;

EID: 0347478167     PISSN: 0954898X     EISSN: None     Source Type: Journal    
DOI: 10.1088/0954-898X_14_2_306     Document Type: Article

References (76)

1. Amari S and Maginu K 1988 Statistical neurodynamics of associative memory Neural Networks 1 63-73
2. Battaglia F P and Treves A 1998 Attractor neural networks storing multiple space representations: a model for hippocampal place fields Phys. Rev. E 58 7738-53
3. Bengio Y, Simard P and Frasconi P 1994 Learning long-term dependencies with gradient descent is difficult IEEE Trans. Neural Networks 5 157-66
4. Bennett M, Gibson W and Robinson J 1994 Dynamics of CA3 pyramidal neurons autoassociative memory network in the hippocampus Phil. Trans. R. Soc. B 343 167-87
5. Bibbig A, Wennekers Th and Palm G 1995 A neural network model of the cortico-hippocampal interplay and the representation of contexts Behav. Brain Res. 66 169-75
6. Bibbig A, Wennekers Th and Palm G 1996 A neural network model of the cortico-hippocampal interplay: contexts and generalization Eng. Appl. Artif. Intell. 9 145-51
7. Bliss T V and Lomo T 1973 Long-lasting potentiation of synaptic transmission in the dentate area of the anaesthetized rabbit following stimulation of the perforant path J. Physiol. (Lond.) 232 331-56
8. Blum K I and Abbott L F 1996 A model of spatial map formation in the hippocampus of the rat Neural Comput. 8 85-93
9. Buckingham J and Willshaw D 1992 Performance characteristics of the associative net Network: Comput. Neural Syst. 3 407-14
10. Buckingham J and Willshaw D 1993 On setting unit thresholds in an incompletely connected associative net Network: Comput. Neural Syst. 4 441-59
11. Dahl D and Winson J 1985 Action of nerepinephrine in the dentate gyrus: I. Stimulation of locus coeruleus Exp. Brain. Res. 59 491-6
12. Doboli S and Minai A A 2000 Network capacity for network attractor computation Proc. IJCNN'2000 (Como, Italy, 2000)
13. Doboli S and Minai A A 2001 Progressive attractor selection in latent attractor networks Proc. IJCNN'2001 (Washington, DC, 2001)
14. Doboli S and Minai A A 2002 Latent attractor selection in the presence of irrelevant stimuli Proc. IJCNN'2002 (Honolulu, Hawaii, 2002)
15. Doboli S, Minai A A and Best P J 1999 A comparison of context-dependent hippocampal place codes in 1-layer and 2-layer recurrent neural networks Proc. Computational Neuroscience Conf. (CNS'99)
16. Doboli S, Minai A A and Best P J 1999 Generating smooth context-dependent representations Proc. IJCNN'99 (Washington, DC, 1999)
17. Doboli S, Minai A A and Best P J 1999 A latent attractors model of context selection in the dentate gyrus-hilus system Neurocomputing 26/27 671-6
18. Doboli S, Minai A A and Best P J 2000 Latent attractors: a model for context-dependence place representations in the hippocampus Neural Comput. 12 1009-43
19. Elman J L 1990 Finding structure in time Cogn. Sci. 14 179-211
20. Frasconi P and Gori M 1996 Computational capabilities of local-feedback recurrent networks acting as finite-state machines IEEE Trans. Neural Networks 7 1521-5
21. Frasconi P, Gori M and Soda G 1992 Local feedback multilayered metworks Neural Comput. 4 120-30
22. Gibson W G and Robinson J 1992 Statistical analysis of the dynamics of a sparse associative memory Neural Networks 5 645-61
23. Giles C L, Miller C B, Chen D, Chen H H, Sun G Z and Lee Y C 1992 Learning and extracting finite state automata with second-order recurrent neural networks Neural Comput. 4 393-405
24. Golomb D, Rubin N and Sompolinsky H 1990 Willshaw model: associative memory with sparse coding and low firing rates Phys. Rev. A 41 1843-54
25. Graham B and Willshaw D 1995 Improving recall from an associative memory Biol. Cybern. 72 337-46
26. Graham B and Willshaw D 1997 Capacity and information efficiency of the associative net Network: Comput. Neural Syst. 8 35-54
27. Grossberg S 1988 Neural Networks and Natural Intelligence (Cambridge, MA: MIT Press)
28. Harley C, Milway J S and Lacaille J-C 1989 Locus coeruleus potentiation of dentate gyrus responses: evidence for two systems Brain Res. Bull. 22 643-50
29. Hasselmo M E, Schnell E and Barkai E 1995 Dynamics of learning and recall at excitatory recurrent synapses and cholinergic modulation in hippocampal region CA3 J. Neurosci. 15 5249-62
30. Hertz J, Krogh A and Palmer R G 1990 Introduction to the Theory of Neural Computation (Reading, MA: Addison-Wesley)
31. Hill A J and Best P J 1981 The effect of deafness and blindness on the spatial correlates of hippocampal unit activity in the rat Exp. Neurol. 74 204-7
32. Hopfield J J 1982 Neural networks and physical systems with emergent collective computational abilities Proc. Natl Acad. Sci. USA 79 2554-8
33. Jordan M I 1986 Attractor dynamics and parallelism in a connectionist sequential machine Proc. 8th Conf. the Cognitive Science Society (Lawrence Elbaum) pp 531-46
34. Kitchigina V, Vankov A, Harley C and Sara S J 1997 Novelty-elicited, noradrenaline-dependent enhancement of excitability in the dentate-gyrus Eur. J. Neurosci. 9 41-7
35. Kohonen T 1989 Self-Organization and Associative Memory (Berlin: Springer)
36. Kosko B 1988 Bidirectional associative memories IEEE Trans. Syst., Man. Cybern. 18 49-60
37. Kudrimoti H S, Barnes C A and McNaughton B L 1999 Reactivation of hippocampal cell assemblies: effects of behavioural state, experience, and EEG dynamics J. Neurosci. 19 4090-101
38. Leung C-S, Chan L-W and Lai E 1995 Stability, capacity, and statistical dynamics of second-order bidirectional associative memory IEEE Trans. Syst., Man Cybern. 25 1414-24
39. Levy W B 1989 A computational approach to hippocampal function Computational Models of Learning in Simple Neural Systems ed R D Hawkins and G H Bower (San Diego, CA: Academic) pp 243-305
40. Levy W B 1996 A sequence predicting CA3 is a flexible associator that learns and uses context to solve hippocampal-like tasks Hippocampus 6 579-91
41. Levy W B and Steward O 1979 Synapses as associative memory elements in the hippocampal formation Brain Res. 175 233-45
42. Levy W B and Wu X 1996 The relationship of local context cues to sequence length memory capacity Network: Comput. Neural Syst. 7 371-84
43. Lin T, Horne B G and Giles C L 1998 How embedded memory in recurrent neural network architectures helps learning long-term temporal dependencies Neural Networks 11 861-8
44. Lin T, Horne B G, Tino P and Giles C L 1996 Learning long-term dependencies in NARX recurrent neural networks IEEE Trans. Neural Networks 7 1329
45. Lukashin A V and Georgopoulos A P 1993 A dynamical neural network model for motor cortical activity during movement: population coding of movement trajectories Biol. Cybern. 69 517-24
46. Markus E J, Qin Y-L, McNaughton B L and Barnes C A 1994 Place fields are affected by behavioural and spatial constraints Cogn. Neurosci. Soc. Abstr. 1 91
47. Marr D 1971 Simple memory: a theory for archicortex Phil. Trans. R. Soc. B 262 23-81
48. McNaughton B L and Morris R G M 1987 Hippocampal synaptic enhancement and storage within a distributed memory system Trends Neurosci. 10 408-15
49. Mehta M, Barnes C A and McNaughton B L 1997 Experience-dependent, asymmetric expansion of hippocampal place fields Proc. Natl Acad. Sci. USA 94 8918-21
50. Minai A A 1997 Covariance learning of correlated patterns in competitive networks Neural Comput. 9 667-81
51. Minai A A, Barrows G L and Levy W B 1994 Disambiguation of pattern sequences with recurrent networks Proc. WCNN (San Diego, CA) vol 4 pp 176-80
52. Minai A A and Best P J 1998 Encoding spatial context: a hypothesis on the function of the dentate gyrus-hilus system Proc. Int. Joint Conf. on Neural Networks (Anchorage) pp 587-92
53. Mozer M C 1992 Induction of multiscale temporal structure Advances in Neural Information Processing Systems vol 4 pp 275-82
54. Muller R U and Kubie J L 1987 The effects of changes in the environment on the spatial firing properties of hippocampal place cells J. Neurosci. 7 1951-68
55. Muller R U, Kubie J L and Ranck J B Jr 1987 Spatial firing patterns of hippocampal complex-spike cells in a fixed environment J. Neurosci. 7 1935-50
56. O'Keefe J and Dostrovsky J 1971 The hippocampus as a spatial map: preliminary evidence from unit activity in the freely moving rat Brain Res. 34 171-5
57. O'Keefe J and Nadel L 1978 The Hippocampus as a Cognitive Map (Oxford: Clarendon)
58. O'Keefe J and Speakman A 1987 Single unit activity in the rat hippocampus during a spatial memory task Exp. Brain Res. 68 1-27
59. Palm G 1980 On associative memory Biol. Cybern. 36 19-31
60. Palm G 1991 Memory capacities for local rules for synaptic modification Concepts Neurosci. 2 97-128
61. Patton P E and McNaughton B L 1995 Connection matrix of the hippocampal formation: I. The dentate gyrus Hippocampus 5 245-86
62. Pearlmutter B A 1989 Learning state space trajectories in recurrent neural networks Neural Comput. 1 263-9
63. Quirk G J, Muller R U and Kubie J L 1990 The firing of hippocampal place cells in the dark depends on the rat's recent experience J. Neurosci. 10 2008-17
64. Redish A D and Touretzky D S 1998 The role of the hippocampus in solving the Morris water maze Neural Comput. 10 73-111
65. Reiss M and Taylor J G 1991 Storing temporal sequences Neural Networks 4 773-87
66. Rolls E T 1989 The representation and storage of information in neuronal networks in the primate cerebral cortex and hippocampus The Computing Neuron ed R Durbin, C Miall and G Mitchison (Reading, MA: Addison-Wesley) pp 125-59
67. Samsonovich A and McNaughton B L 1997 Path integration and cognitive mapping in a continuous attractor neural network model J. Neurosci. 17 5900-20
68. Servan-Schreiber D, Cleereman A and McClelland J L 1989 Learning sequential structure in simple recurrent networks Advances in Neural Information Processing Systems I pp 643-52
69. Skaggs W E and McNaughton B L 1998 Spatial firing properties of hippocampal CA1 populations in an environment containing two visually identical regions J. Neurosci. 15 811-20
70. Sommer F T and Palm G 1999 Improved bidirectional retrieval of sparse patterns stored by Hebbian learning Neural Networks 12 281-97
71. Tanila H 1999 Hippocampal place cells can develop distinct representations of two visually identical environments Hippocampus 9 235-46
72. Tsodyks M and Sejnowski T 1995 Associative memory and hippocampal place cells Int. J. Neural Syst. 6 81-6
73. Vogel D D and Boos W 1997 Sparsely connected, hebbian networks with strikingly large storage capacities Neural Networks 10 671-82
74. Williams R J and Zipser D 1989 A learning algorithm for continually running fully recurrent neural networks Neural Comput. 1 270-80
75. Willshaw D, Buneman O P and Longuet-Higgins H C 1969 Non-holographic associative memory Nature 222 960-2
76. Wilson M A and McNaughton B L 1993 Dynamics of the hippocampal ensemble code for space Science 261 1055-8