RT info:eu-repo/semantics/doctoralThesis
T1 Analysis and correlation between brain signals and genetic data for the characterization of the Alzheimer's disease
A1 Maturana Candelas, Aarón
A2 Universidad de Valladolid. Escuela de Doctorado
K1 Neurociencias
K1 Alzheimer's disease
K1 Enfermedad de Alzheimer
K1 Electroencephalogram
K1 Electroencefalograma
K1 Genetics
K1 Genética
K1 Biosignal processing
K1 Procesado de bioseñal
K1 33 Ciencias Tecnológicas
AB Alzheimer's disease (AD) is a neurodegenerative disorder characterized by disabling symptomatology that aggravates gradually along its progression in the form of dementia. This syndrome greatly affects cognitive capabilities that involve memory, behavior, and thinking. The more advanced states of dementia are accompanied by devastating deterioration in overall brain functions, even including language and movement. This brings the patients to a fully-dependent condition, making them unable to engage in basic cognitive faculties that allow daily-basis tasks. The increase in life expectancy has resulted in a higher prevalence of neurodegenerative diseases, such as AD, which has become a public health concern. For this reason, an understanding of the mechanisms that lead to AD is of paramount importance. Although the current state of the art associates AD with a compilation of biochemical and functional changes in the brain, the actual causes that originate AD are yet to be discerned.In the present Doctoral Thesis, the electroencephalography (EEG) activity in AD has been characterized using different frameworks that incorporate genetic aspects. These perspectives are aimed at obtaining new insights into the relation between EEG alterations and neurodegeneration caused by AD. They include a multiscale entropy analysis to estimate EEG complexity; a bispectral analysis in order to quantify non-linear interactions between specific frequency components; a spectral analysis in carriers of risk and protective alleles of two genes implicated in cell debris clearance; and finally, a multiplex network analysis in carriers of risk and protective alleles in seven variants of the tau-encoding gene, a protein closely related with AD. These procedures were applied to the resting-state EEG acquired from participants previously categorized in five study groups describing the AD continuum, from healthy control subjects to severe AD patients.The results obtained along the Doctoral Thesis revealed several insights that provide hints about the association between AD and alterations in brain electrical activity. First, it was confirmed that neurodegeneration caused by AD is associated with continuous deterioration in brain mechanisms that involve information processing. This can be suggested by the significant changes in EEG complexity and bispectral features as AD severity increases. And secondly, it has been demonstrated that brain electrical activation is sensitive to minimal genetic variations associated with AD biochemical biomarkers. In addition, these implications may be more notorious in different cognitive conditions depending on the affected neurophysiological mechanism. Based on the aforementioned findings, this work represents an advance in the understanding of AD at an essential level. Besides, it contributes to elucidating significant relationships between brain electrical activation and aspects, both biological and computational, that could inspire future work in the field of AD prevention.
YR 2024
FD 2024
LK https://uvadoc.uva.es/handle/10324/71395
UL https://uvadoc.uva.es/handle/10324/71395
LA eng
NO Escuela de Doctorado
DS UVaDOC
RD 24-nov-2024