Literature DB >> 760831

A neural network model for the development of direction selectivity in the visual cortex.

T Nagano, M Fujiwara.   

Abstract

A neural network model is proposed to explain the development of direction selectivity of cortical cells. The model is constructed under the following three hypotheses that are very plausible from recent neurophysiological findings. (1) Direction selectivity is developed by modifiable inhibitory synapses. (2) It results not from the direct convergence of many excitatory inputs from LGN cells but from cortical neural networks. (3) Direction-selective mechanism is independent of orientation-selective mechanism.--The model was simulated on a computer for a few kinds of inhibitory connections and initial conditions. The results were consistent with neurophysiological facts not only for normal cats but for cats reared in an abnormal visual environment.

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Year:  1979        PMID: 760831     DOI: 10.1007/bf00337445

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


  20 in total

1.  Cognitron: a self-organizing multilayered neural network.

Authors:  K Fukushima
Journal:  Biol Cybern       Date:  1975-11-05       Impact factor: 2.086

2.  Direction selectivity of simple striate cells: properties and mechanism.

Authors:  A W Goodwin; G H Henry; P O Bishop
Journal:  J Neurophysiol       Date:  1975-11       Impact factor: 2.714

3.  Inhibitory processes underlying the directional specificity of simple, complex and hypercomplex cells in the cat's visual cortex.

Authors:  A M Sillito
Journal:  J Physiol       Date:  1977-10       Impact factor: 5.182

4.  Development of Specificity in the Cat Visual Cortex.

Authors:  Rafael Pérez; Leon Glass; Robert Shlaer
Journal:  J Math Biol       Date:  2017-03-15       Impact factor: 2.259

5.  An intracellular analysis of visual cortical neurones to moving stimuli: response in a co-operative neuronal network.

Authors:  O D Creutzfeldt; U Kuhnt; L A Benevento
Journal:  Exp Brain Res       Date:  1974       Impact factor: 1.972

6.  Single units in visual cortex of kittens reared in stroboscopic illumination.

Authors:  C R Olson; J D Pettigrew
Journal:  Brain Res       Date:  1974-04-19       Impact factor: 3.252

7.  Receptive field analysis: responses to moving visual contours by single lateral geniculate neurones in the cat.

Authors:  B Dreher; K J Sanderson
Journal:  J Physiol       Date:  1973-10       Impact factor: 5.182

8.  Quantitative studies of single-cell properties in monkey striate cortex. V. Multivariate statistical analyses and models.

Authors:  P H Schiller; B L Finlay; S F Volman
Journal:  J Neurophysiol       Date:  1976-11       Impact factor: 2.714

9.  Visual experience modifies distribution of horizontally and vertically oriented receptive fields in cats.

Authors:  H V Hirsch; D N Spinelli
Journal:  Science       Date:  1970-05-15       Impact factor: 47.728

10.  Cats raised in a one-directional world: effects on receptive fields in visual cortex and superior colliculus.

Authors:  M Cynader; N Berman; A Hein
Journal:  Exp Brain Res       Date:  1975-03-27       Impact factor: 1.972

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  4 in total

1.  Self-stabilization of neuronal networks. I. The compensation algorithm for synaptogenesis.

Authors:  I E Dammasch; G P Wagner; J R Wolff
Journal:  Biol Cybern       Date:  1986       Impact factor: 2.086

2.  Self-organization of the velocity selectivity of a directionally selective neural network.

Authors:  K Miura; K Kurata; T Nagano
Journal:  Biol Cybern       Date:  1995-10       Impact factor: 2.086

3.  A self-organizing neural network model for the development of complex cells.

Authors:  T Nagano; K Kurata
Journal:  Biol Cybern       Date:  1981       Impact factor: 2.086

4.  Spike-based synaptic plasticity and the emergence of direction selective simple cells: simulation results.

Authors:  N J Buchs; W Senn
Journal:  J Comput Neurosci       Date:  2002 Nov-Dec       Impact factor: 1.621

  4 in total

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