Abstract

CARRILLO-MEDINA, José Luis  and  ESPINEL-MENA, Gonzalo Patricio. Heterogeneous networks of neurons that recognize signatures neural. Dyna rev.fac.nac.minas [online]. 2017, vol.84, n.201, pp.27-33. ISSN 0012-7353.  https://doi.org/10.15446/dyna.v84n202.60299.

Experimental results demonstrate that cells of different living neural system they can identify univocally their output signals through specific neural signatures. The functional meaning of these signatures is still unclear, the existence of cellular mechanisms to identify the source of individual signals and contextualize incoming messages can be a powerful information processing strategy for the nervous system. We recently built different models to study the ability of a neural network to encode and process information based on the emission and recognition of specific signature with homogeneous populations where the neurons in the network will be able to recognize and emit the same firms with the same probability. In this paper, we further analyze the features that can influence on the information processing ability when we vary the probability of recognition that each neuron has for different signatures in networks heterogeneous. Simulations show the increases the dynamic properties of the network.

Keywords : Neural signature; processing based on signal identification; self-organizing neural network; heterogeneous populations.

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