Análise da dinâmica neural na via acústico-límbica frente à tarefa de aprendizagem associativa em modelo experimental de laboratório

Detalhes bibliográficos
Ano de defesa: 2023
Autor(a) principal: Matheus Victor Ramos dos Anjos
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Minas Gerais
Brasil
ENG - DEPARTAMENTO DE ENGENHARIA ELÉTRICA
Programa de Pós-Graduação em Engenharia Elétrica
UFMG
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://hdl.handle.net/1843/63991
Resumo: This work presents the use of time-domain high-order spectral analysis to identify changes in the limbic acoustic neural network following an associative learning task in rodents. It has been demonstrated that during auditory fear conditioning tasks, potentials evoked in the inferior colliculus exhibit oscillations at the same frequency as the modulating frequency of the sound stimulus used as conditioned stimulus, presenting increased power and synchronism for that frequency. In other brain substrates, predominant increases are observed in the θ frequency band, between 4 to 8 Hz, in addition to significant increases in the γ band. The present work discusses the advantages and disadvantages of using time-domain high-order spectral analysis compared to traditional techniques for identifying attributes related to neural plasticity, such as increases in phase synchrony and power. It is noteworthy that time-domain high-order spectral analysis can provide valuable information about possible nonlinearities and frequency coupling. The work provides an overview of the mathematical foundations of each technique, emphasizing the potential of time-domain high-order spectral analysis as a valuable tool for analyzing electrophysiological recordings. Two different databases were studied, one published, whose records were made only in the midbrain of rats, in this case, the inferior colliculus (IC), [Simões et al., 2020] and another, unpublished, whose records were made throughout the entire route limbic acoustic system of mice, such as inferior colliculus, amygdaloid complex, and medial prefrontal cortex. The results obtained contain valuable information for understanding the complex dynamics of neural networks, which enables the identification of the underlying mechanisms of neural plasticity.