Sincronização de Disparos Neuronais no Córtex

• Ano de defesa: 2016
• Autor(a) principal: Lameu, Ewandson Luiz
• Orientador(a): Batista, Antonio Marcos
• Banca de defesa: Szezech Júnior, José Danilo , Souza, Silvio Luiz Thomaz de , Souza, Gelson Biscaia de , Tusset, Angelo Marcelo
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: UNIVERSIDADE ESTADUAL DE PONTA GROSSA
• Programa de Pós-Graduação: Programa de Pós-Graduação em Ciências
• Departamento: Fisica
• País: BR
• Palavras-chave em Português: Sincronização; redes neuronais; mapas de Rulkov; supressão da sincronização
• Palavras-chave em Inglês: synchronization; neural networks; Rulkov maps; suppression of synchronization
• Área do conhecimento CNPq: CNPQ::CIENCIAS EXATAS E DA TERRA::FISICA
• Link de acesso: http://tede2.uepg.br/jspui/handle/prefix/862

In this thesis we present a theoretical model of a neural network based on real anatomical structure of connections between cat’s cerebral cortex areas. This anatomical network contains 65 cortical areas organized into four regions called visual, auditory, somatosensory-motor and frontolimbic. We analize for which probabilities of connections the proposed network approaches with greater fidelity the real anatomical network. To describe the neuron dynamics we use a system known as Rulkov bidimensional map, which is a phenomenological model that simulates the changes in the neuronal membrane potential. For the coupling between neurons we consider electrical and chemical synapses. Then, we study the phenomenon of synchronization of neuronal firing due to its relationship with some neurological disorders such as Parkinson’s disease and epilepsy. In addition to seeking the cause of these disorders, the study of effective techniques to prevent such behavior becomes indispensable. In light of this, we propose three methods of applying external perturbations over the system with the aim of suppress synchronization. The first of these disorders simulates a stimulus by light that is capable of inducing a neuron to have a spike, the second perturbation used was the introduction of a periodic electrical current on the network, and the third was based on reinjection of an electric signal collected from the system itself. We show the coupling intervals where disturbances are able to suppress the synchrony and evaluate which of them has higher efficiency.