Literature DB >> 3676357

A cognitive and associative memory.

S Shinomoto1.   

Abstract

By introducing a physiological constraint in the auto-correlation matrix memory, the system is found to acquire an ability in cognition i.e. the ability to identify an input pattern by its proximity to any one of the stored memories. The physiological constraint here is that the attribute of a given synapse (i.e. excitatory or inhibitory) is uniquely determined by the neuron it belongs. Thus the synaptic coupling is generally not symmetric. Analytical and numerical analyses revealed that the present model retrieves a memory if an input pattern is close to the pattern of the stored memories; if not, it gives a clear response by going into a special mode where almost all neurons are in the same state in each time step. This uniform mode may be stationary or periodic, depending on whether or not the number of the excitatory neurons exceeds the number of inhibitory neurons.

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Year:  1987        PMID: 3676357     DOI: 10.1007/bf00364151

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  12 in total

1.  Outline of a theory of thought-processes and thinking machines.

Authors:  E R CAIANIELLO
Journal:  J Theor Biol       Date:  1961-04       Impact factor: 2.691

2.  Associative recall of images.

Authors:  T Kohonen; E Reuhkala; K Mäkisara; L Vainio
Journal:  Biol Cybern       Date:  1976       Impact factor: 2.086

3.  Neural theory of association and concept-formation.

Authors:  S I Amari
Journal:  Biol Cybern       Date:  1977-05-17       Impact factor: 2.086

4.  Associative recognition and storage in a model network of physiological neurons.

Authors:  J Buhmann; K Schulten
Journal:  Biol Cybern       Date:  1986       Impact factor: 2.086

5.  A neural network model for selective attention in visual pattern recognition.

Authors:  K Fukushima
Journal:  Biol Cybern       Date:  1986       Impact factor: 2.086

6.  Excitatory and inhibitory interactions in localized populations of model neurons.

Authors:  H R Wilson; J D Cowan
Journal:  Biophys J       Date:  1972-01       Impact factor: 4.033

7.  Neural networks and physical systems with emergent collective computational abilities.

Authors:  J J Hopfield
Journal:  Proc Natl Acad Sci U S A       Date:  1982-04       Impact factor: 11.205

8.  A hierarchical neural network model for associative memory.

Authors:  K Fukushima
Journal:  Biol Cybern       Date:  1984       Impact factor: 2.086

9.  'Unlearning' has a stabilizing effect in collective memories.

Authors:  J J Hopfield; D I Feinstein; R G Palmer
Journal:  Nature       Date:  1983 Jul 14-20       Impact factor: 49.962

10.  Neurons with graded response have collective computational properties like those of two-state neurons.

Authors:  J J Hopfield
Journal:  Proc Natl Acad Sci U S A       Date:  1984-05       Impact factor: 11.205

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  7 in total

1.  A neural network model of the cerebellar cortex performing dynamic associations.

Authors:  F Chapeau-Blondeau; G Chauvet
Journal:  Biol Cybern       Date:  1991       Impact factor: 2.086

2.  A model for neuronal oscillations in the visual cortex. 1. Mean-field theory and derivation of the phase equations.

Authors:  H G Schuster; P Wagner
Journal:  Biol Cybern       Date:  1990       Impact factor: 2.086

3.  Neural networks counting chimes.

Authors:  D J Amit
Journal:  Proc Natl Acad Sci U S A       Date:  1988-04       Impact factor: 11.205

4.  Associative memory neural network with low temporal spiking rates.

Authors:  D J Amit; A Treves
Journal:  Proc Natl Acad Sci U S A       Date:  1989-10       Impact factor: 11.205

5.  A model of cortical memory processing based on columnar organization.

Authors:  T Fukai
Journal:  Biol Cybern       Date:  1994       Impact factor: 2.086

6.  The connectivity of the brain: multi-level quantitative analysis.

Authors:  J M Murre; D P Sturdy
Journal:  Biol Cybern       Date:  1995-11       Impact factor: 2.086

7.  Dynamics and bifurcations of two coupled neural oscillators with different connection types.

Authors:  G N Borisyuk; R M Borisyuk; A I Khibnik; D Roose
Journal:  Bull Math Biol       Date:  1995-11       Impact factor: 1.758

  7 in total

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