Concatenated retrieval of correlated stored information in neural networks

We consider a coupled map lattice defined on a hypercube in M dimensions, taken here as the information space, to model memory retrieval and information association by a neural network. We assume that both neuronal activity and spike timing may carry information. In this model the state of the netwo...

Full description

Saved in:
Bibliographic Details
Published in:Physical review. E, Statistical, nonlinear, and soft matter physics Statistical, nonlinear, and soft matter physics, 2006-10, Vol.74 (4 Pt 1), p.041912-041912, Article 041912
Main Authors: de Almeida, R M C, Espinosa, A, Idiart, M A P
Format: Article
Language:English
Subjects:
Action Potentials - physiology
Computer Simulation
Information Storage and Retrieval - methods
Logistic Models
Long-Term Potentiation - physiology
Memory - physiology
Models, Neurological
Nerve Net - physiology
Neurons - physiology
Statistics as Topic
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We consider a coupled map lattice defined on a hypercube in M dimensions, taken here as the information space, to model memory retrieval and information association by a neural network. We assume that both neuronal activity and spike timing may carry information. In this model the state of the network at a given time t is completely determined by the intensity y(sigma,t) with which the information pattern represented by the integer sigma is being expressed by the network. Logistic maps, coupled in the information space, are used to describe the evolution of the intensity function y(sigma(upper arrow),t) with the intent to model memory retrieval in neural systems. We calculate the phase diagram of the system regarding the model ability to work as an associative memory. We show that this model is capable of retrieving simultaneously a correlated set of memories, after a relatively long transient that may be associated to the retrieving of concatenated memorized patterns that lead to a final attractor.
ISSN:1539-3755
1550-2376
DOI:10.1103/PhysRevE.74.041912