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  1. On bifurcations and chaos in random neural networks.B. Doyon, B. Cessac, M. Quoy & M. Samuelides - 1994 - Acta Biotheoretica 42 (2-3):215-225.
    Chaos in nervous system is a fascinating but controversial field of investigation. To approach the role of chaos in the real brain, we theoretically and numerically investigate the occurrence of chaos inartificial neural networks. Most of the time, recurrent networks (with feedbacks) are fully connected. This architecture being not biologically plausible, the occurrence of chaos is studied here for a randomly diluted architecture. By normalizing the variance of synaptic weights, we produce a bifurcation parameter, dependent on this variance and on (...)
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  • Wave-function and the concept of a nano-mental element of representation.Eric Wallich - 1993 - Acta Biotheoretica 41 (1-2):119-125.
    Scientific endeavour has often tried to localize superior cerebral functions either in areas like the ones described by Broca as being those connected with language in the left hemisphere, or in the huge array of the hundred billion of interconnected neurons. But in this last case the coined description of the grandmother neuron, tends to show humorously that hopes have fallen short of their target.Along the same lines, the specific timing of electric neural activity is known to take place around (...)
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  • Mean-field equations, bifurcation map and chaos in discrete time, continuous state, random neural networks.B. Doyon, B. Cessac, M. Quoy & M. Samuelides - 1995 - Acta Biotheoretica 43 (1-2):169-175.
    The dynamical behaviour of a very general model of neural networks with random asymmetric synaptic weights is investigated in the presence of random thresholds. Using mean-field equations, the bifurcations of the fixed points and the change of regime when varying control parameters are established. Different areas with various regimes are defined in the parameter space. Chaos arises generically by a quasi-periodicity route.
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  • Information processing in neural networks by means of controlled dynamic regimes.François Chapeau-Blondeau - 1995 - Acta Biotheoretica 43 (1-2):155-167.
    This paper is concerned with the modeling of neural systems regarded as information processing entities. I investigate the various dynamic regimes that are accessible in neural networks considered as nonlinear adaptive dynamic systems. The possibilities of obtaining steady, oscillatory or chaotic regimes are illustrated with different neural network models. Some aspects of the dependence of the dynamic regimes upon the synaptic couplings are examined. I emphasize the role that the various regimes may play to support information processing abilities. I present (...)
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