30
Views
1
CrossRef citations to date
0
Altmetric
Original Article

Network capacity analysis for latent attractor computation

&
Pages 273-302 | Received 27 Jun 2002, Published online: 09 Jul 2009

References

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

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.