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Descripción
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| Mild Cognitive Impairment (MCI) is an intermediate state between healthy aging and dementia consisting in a progressive episodic memory loss. The fact that 10% of elderly MCI patients develop Alzheimer?s each year makes it an interesting candidate to reveal some clues about prodromal Alzheimer. In the current work we introduce a novel methodology in the framework of complex networks theory to built up a new kind of functional networks known as Anomalous (also Parenclitic) Networks.Specifically, we perform a statistical analysis in order to construct networks whose links rely on the differences between a group of healthy individuals and a group of patients suffering from MCI. This way we are able to evaluate how the consistency of MCI patients during a memory test is affected by the disease and what are those cortical regions that suffer the most. The application of this methodology ranges from a diversity of brain diseases to any other systems with two (or more) well defined groups. | |
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Internacional
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Si |
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Nombre congreso
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European Conference on Complex Systems [http://www.eccs13.eu] |
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Tipo de participación
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960 |
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Lugar del congreso
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Barcelona |
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Revisores
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Si |
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ISBN o ISSN
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000-00-000-0000-0 |
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DOI
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Fecha inicio congreso
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16/09/2013 |
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Fecha fin congreso
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20/09/2013 |
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Desde la página
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153 |
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Hasta la página
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153 |
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Título de las actas
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ECCS'13 Book of Abstracts [http://www.eccs13.eu/images/site/book_of_abstracts.pdf] |