Mathematical Models of Dynamic Behavior of Individual Neural Networks of Central Nervous System

Abstract : We present mathematical models that describe individual neural networks of the Central Nervous System. Three cases are examined, varying in each case the values of the refractory period and the synaptic delay of a neuron. In the case where both the refractory period and the synaptic delay are bigger than one, we split the population of neurons into sub-groups with their own distinct synaptic delay. It is shown that the proposed approach describes the neural activity of the network efficiently, especially in the case mentioned above. Various examples with different network parameters are presented to investigate the network’s behavior.
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Lazaros Iliadis; Chrisina Jayne. 12th Engineering Applications of Neural Networks (EANN 2011) and 7th Artificial Intelligence Applications and Innovations (AIAI), Sep 2011, Corfu, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-363 (Part I), pp.433-442, 2011, Engineering Applications of Neural Networks. 〈10.1007/978-3-642-23957-1_48〉
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Dimitra-Despoina Pagania, Adam Adamopoulos, Spiridon Likothanassis. Mathematical Models of Dynamic Behavior of Individual Neural Networks of Central Nervous System. Lazaros Iliadis; Chrisina Jayne. 12th Engineering Applications of Neural Networks (EANN 2011) and 7th Artificial Intelligence Applications and Innovations (AIAI), Sep 2011, Corfu, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-363 (Part I), pp.433-442, 2011, Engineering Applications of Neural Networks. 〈10.1007/978-3-642-23957-1_48〉. 〈hal-01571328〉

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