An oscillatory neural network model of sparse distributed memory and novelty detection.

A model of sparse distributed memory is developed that is based on phase relations between the incoming signals and an oscillatory mechanism for information processing. This includes phase-frequency encoding of input information, natural frequency adaptation among the network oscillators for storage of input signals, and a resonance amplification mechanism that responds to familiar stimuli. Simulations of this model show different types of dynamics in response to new and familiar stimuli. The application of the model to hippocampal working memory is discussed.

[1]  G. Paxinos.  The Rat nervous system , 1985 .

[2]  Roman Borisyuk,et al.  Dynamics of neural networks with a central element , 1999, Neural Networks.

[3]  L. Squire.  Memory and the hippocampus: a synthesis from findings with rats, monkeys, and humans. , 1992, Psychological review.

[4]  Frank C. Hoppensteadt.  Signal Processing by Model Neural Networks , 1992, SIAM Rev..

[5]  Carme Torras i Genis,et al.  Neural Network Model with Rhythm-Assimilation Capacity , 1986 .

[6]  M. Witter,et al.  Entorhinal-Hippocampal Interactions Revealed by Real-Time Imaging , 1996, Science.

[7]  E. Izhikevich,et al.  Weakly connected neural networks , 1997 .

[8]  R M Borisyuk,et al.  Memorizing and recalling spatial-temporal patterns in an oscillator model of the hippocampus. , 1998, Bio Systems.

[9]  Roman Borisyuk,et al.  Oscillatory models of the hippocampus: A study of spatio-temporal patterns of neural activity , 1999, Biological Cybernetics.

[10]  Frank C. Hoppensteadt,et al.  An introduction to the mathematics of neurons , 1986 .

[11]  Antonio R. Damasio,et al.  The Brain Binds Entities and Events by Multiregional Activation from Convergence Zones , 1989, Neural Computation.

[12]  Jean-Baptiste Lully,et al.  The collected works , 1996 .

[13]  Dr. Robert Miller.  Cortico-Hippocampal Interplay and the Representation of Contexts in the Brain , 1991, Studies of Brain Function.

[14]  Bard Ermentrout,et al.  Learning of Phase Lags in Coupled Neural Oscillators , 1994, Neural Computation.

[15]  O. Vinogradova.  Expression, control, and probable functional significance of the neuronal theta-rhythm , 1995, Progress in Neurobiology.

[16]  E. Lewis.  An Introduction to the Mathematics of Neurons , 1987, Trends in Neurosciences.