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Connectome: Graph theory application in functional brain network architecture

Network science and graph theory applications have recently spread widely to help in understanding how human cognitive functions are linked to neuronal network structure, thus providing a conceptual frame that can help in reducing the analytical brain complexity and underlining how network topology...

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Detalles Bibliográficos
Autores principales: Vecchio, Fabrizio, Miraglia, Francesca, Maria Rossini, Paolo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6123924/
https://www.ncbi.nlm.nih.gov/pubmed/30214997
http://dx.doi.org/10.1016/j.cnp.2017.09.003
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author Vecchio, Fabrizio
Miraglia, Francesca
Maria Rossini, Paolo
author_facet Vecchio, Fabrizio
Miraglia, Francesca
Maria Rossini, Paolo
author_sort Vecchio, Fabrizio
collection PubMed
description Network science and graph theory applications have recently spread widely to help in understanding how human cognitive functions are linked to neuronal network structure, thus providing a conceptual frame that can help in reducing the analytical brain complexity and underlining how network topology can be used to characterize and model vulnerability and resilience to brain disease and dysfunction. The present review focuses on few pivotal recent studies of our research team regarding graph theory application in functional dynamic connectivity investigated by electroencephalographic (EEG) analysis. The article is divided into two parts. The first describes the methodological approach to EEG functional connectivity data analysis. In the second part, network studies of physiological aging and neurological disorders are explored, with a particular focus on epilepsy and neurodegenerative dementias, such as Alzheimer's disease.
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spelling pubmed-61239242018-09-13 Connectome: Graph theory application in functional brain network architecture Vecchio, Fabrizio Miraglia, Francesca Maria Rossini, Paolo Clin Neurophysiol Pract Reviews, Expert Opinions and Guideline Network science and graph theory applications have recently spread widely to help in understanding how human cognitive functions are linked to neuronal network structure, thus providing a conceptual frame that can help in reducing the analytical brain complexity and underlining how network topology can be used to characterize and model vulnerability and resilience to brain disease and dysfunction. The present review focuses on few pivotal recent studies of our research team regarding graph theory application in functional dynamic connectivity investigated by electroencephalographic (EEG) analysis. The article is divided into two parts. The first describes the methodological approach to EEG functional connectivity data analysis. In the second part, network studies of physiological aging and neurological disorders are explored, with a particular focus on epilepsy and neurodegenerative dementias, such as Alzheimer's disease. Elsevier 2017-10-24 /pmc/articles/PMC6123924/ /pubmed/30214997 http://dx.doi.org/10.1016/j.cnp.2017.09.003 Text en © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Reviews, Expert Opinions and Guideline
Vecchio, Fabrizio
Miraglia, Francesca
Maria Rossini, Paolo
Connectome: Graph theory application in functional brain network architecture
title Connectome: Graph theory application in functional brain network architecture
title_full Connectome: Graph theory application in functional brain network architecture
title_fullStr Connectome: Graph theory application in functional brain network architecture
title_full_unstemmed Connectome: Graph theory application in functional brain network architecture
title_short Connectome: Graph theory application in functional brain network architecture
title_sort connectome: graph theory application in functional brain network architecture
topic Reviews, Expert Opinions and Guideline
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6123924/
https://www.ncbi.nlm.nih.gov/pubmed/30214997
http://dx.doi.org/10.1016/j.cnp.2017.09.003
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