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Brain Connectivity and Graph Theory Analysis in Alzheimer’s and Parkinson’s Disease: The Contribution of Electrophysiological Techniques

Academic Article
Publication Date:
2022
abstract:
In recent years, applications of the network science to electrophysiological data have increased as electrophysiological techniques are not only relatively low cost, largely available on the territory and non-invasive, but also potential tools for large population screening. One of the emergent methods for the study of functional connectivity in electrophysiological recordings is graph theory: it allows to describe the brain through a mathematic model, the graph, and provides a simple representation of a complex system. As Alzheimer’s and Parkinson’s disease are associated with synaptic disruptions and changes in the strength of functional connectivity, they can be well de-scribed by functional connectivity analysis computed via graph theory. The aim of the present review is to provide an overview of the most recent applications of the graph theory to electrophysiological data in the two by far most frequent neurodegenerative disorders, Alzheimer’s and Parkin-son’s diseases.
Iris type:
1.1 Articolo in rivista
Keywords:
Alzheimer; EEG; graph theory; MEG; Parkinson
List of contributors:
Miraglia, F.; Vecchio, F.; Pappalettera, C.; Nucci, L.; Cotelli, M.; Judica, E.; Ferreri, F.; Rossini, P. M.
Authors of the University:
MIRAGLIA FRANCESCA
VECCHIO FABRIZIO
Handle:
https://iris.uniecampus.it/handle/11389/36876
Published in:
BRAIN SCIENCES
Journal
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