Conectividade funcional do cérebro no envelhecimento : uma avaliação utilizando ressonância magnética funcional do estado de repouso e teoria de grafos

Detalhes bibliográficos
Ano de defesa: 2020
Autor(a) principal: Maulaz, Carolina Moreira lattes
Orientador(a): Silva, Ana Maria Marques da lattes
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Pontifícia Universidade Católica do Rio Grande do Sul
Programa de Pós-Graduação: Programa de Pós-Graduação em Engenharia Elétrica
Departamento: Escola Politécnica
País: Brasil
Palavras-chave em Português:
Palavras-chave em Inglês:
AD
MCI
Área do conhecimento CNPq:
Link de acesso: http://tede2.pucrs.br/tede2/handle/tede/9408
Resumo: Studies suggests that healthy aging (ES) and certain neurological diseases, such as Alzheimer's disease (AD) and mild cognitive impairment (MCI), affects brain functional connectivity. Graph Theory (GT) metrics allows us to analyze ruptures in the brain functional connectivity. However, researchers has been preferentially exploring transversal studies. The general objective of this work was to investigate the evolution of brain connectivity in individuals with healthy aging and cognitive decline, based on resting state functional magnetic resonance imaging (rs-fMRI) and using graph metrics. The data was divided into two groups, stable (EES-EES and EMCI-EMCI) and converter (ES-MCI and MCI-AD). The longitudinal analysis was carried out between each evolution over time, then crosswise compared healthy individuals between the stable and converting group, and the same process was performed for individuals with MCI.The processing was implemented in SPM12-MATLAB performed in the CONN Toolbox. The networks analyzed were parietal, sensory motor, visual, language, default mode network, dorsal attention and salience. The GT metrics chosen to describe the main topological characteristics of the networks were: characteristic path length, global efficiency, local efficiency, clustering coefficient and degree. The results indicateds a decrease in the strength of functional connectivity in individuals with MCI and AD compared with healthy aging. In healthy aging individuals, was identified that local efficiency metric can be used as a possible biomarker between those who remain stable and those who convert. In MCI individuals, a metric was not identified, but a set of metrics that vary between converting and stable groups. The analysis of all networks in the resting state allowed for a better characterization of the groups, enabling the differentiation between stable healthy individuals and those who convert to cognitive decline over time.