Análise de sinais eletrofisiológicos obtidos por matrizes microeletrodo, calibradas por testes estocásticos descritivos da estrutura de densidade de probabilidade

• Ano de defesa: 2021
• Autor(a) principal: Faria, Vinícius Naves Rezende
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Uberlândia; Brasil; Programa de Pós-graduação em Engenharia Elétrica
• Palavras-chave em Português: Matiz Microeletrodos MEA; Cultura Neuronal; Ruído Biológico; Guassianidade; Estacionariedade; MEA Microelectrodes Array; Neuronal Culture; Biological Noise; Gaussianity and Stationarity; CNPQ::ENGENHARIAS::ENGENHARIA BIOMEDICA; Engenharia elétrica
• Link de acesso: https://repositorio.ufu.br/handle/123456789/32690; http://doi.org/10.14393/ufu.te.2021.404

The present work aims to present, discuss, and quantitatively characterize the neuronal cultures signal, captured by a calibrated MEA60 system, taking into account the temporal evolution of electrical activity along the geometric regions of this device; in addition to applying the same analysis to the noise component of this signal, composed of instrumentation noise and biological noise. Therefore, the proposed methodology comprises the capture of these signals by MEA equipment properly calibrated under concepts of metrology and uncertainty of determination, classical analysis based on spikes and bursts and, finally, a description of the probability density structure through the quantification of Gaussianity (percentage of non-Gaussian segments - PSNG) and stationarity (percentage of non-stationary segments - PSNE). The quantifiers linked to the power spectral density, first order, prove to be statistically weak in characterizing as components of the MEA signal. However, PSNG and PSNE were able to characterize as growth stages of neuronal cell culture, as well as to indicate potential differentiation between the stretches of biological noise intrinsic to this signal. This is reinforced by the result of the cluster analysis. In the analysis of the biological noise component, there is an increase in PSNE in the phases of cell onset and death in which the statistical characteristics vary over time and carried important non-random information in the stationary or Gaussian sense. Finally, a cell death phase, a biologically important phase regarding biochemical and cellular reactions, natural to the biological cell death process, was a phase that showed more correlations between the variables studied, presenting a certain biological organization.