Análise espectral do tratamento via LTP em ratos com epilepsia induzida

Detalhes bibliográficos
Ano de defesa: 2019
Autor(a) principal: CANDEIAS, Eugenio Luiz Carneiro Valdez lattes
Orientador(a): STOSIC, Borko
Banca de defesa: FIGUEIRÊDO, Pedro Hugo de, MATIAS, Fernanda Selingardi
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal Rural de Pernambuco
Programa de Pós-Graduação: Programa de Pós-Graduação em Física Aplicada
Departamento: Departamento de Física
País: Brasil
Palavras-chave em Português:
Área do conhecimento CNPq:
Link de acesso: http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/8523
Resumo: Epilepsy is a set of diseases whose point in common is the epileptic seizure, and the central nervous system has mechanisms that protect the brain against epileptic hypersynchronism. These mechanisms, which are a set of metabolic, hemodynamic and synaptic adaptions, are called endogenous anticonvulsivant system (SAEs). Some studies shows that the substantia nigra pars reticulata (SNPr) has a strong relevance in the control of seizures, that both SNPr inhibition and striatum (STR) excitation are anticonvulsivants. Our group realizes a LTP protocol in Long-Evans rats by high frequency electrical stimulation on STR and record the evoked potential in the SNPr, STR and hippocampus (HIPO). All behavioral results were promising, such as a quantity of walked squares and self-cleaning in the experimental group, among others. In this work we did a spectral analysis, applying techniques of neural data analysis in the local field potential (LFP) - of the three regions - collected in the experiment. We use the fast Fourier transform (FFT) to identify the noise level in the data set, when necessary we apply a reject filter to eliminate the powerline interference (60 Hz). To identity the causality between SNPr, STR and HIPO regions, we use techniques of signal processing, such as coherence and Granger causality and we could verify a greater causality when the SNPr was involved. We confirm our data using another technique consisting of surrogating the data sequence, breaking the temporal correlation. Without this correlation, the magnitude of our results had significant declines.