Searching for signs of aging and dementia in EEG through network analysis

Francesca Miraglia; Fabrizio Vecchio; Paolo Maria Rossini

doi:10.1016/j.bbr.2016.09.057

Searching for signs of aging and dementia in EEG through network analysis

Francesca Miraglia, Fabrizio Vecchio, Paolo Maria Rossini

Istituto San Raffaele Pisana

Research output: Contribution to journal › Review article › peer-review

Abstract

Graph theory applications had spread widely in understanding how human cognitive functions are linked to dynamics of neuronal network structure, providing a conceptual frame that can reduce the analytical brain complexity. This review summarizes methodological advances in this field. Electroencephalographic functional network studies in pathophysiological aging will be presented, focusing on neurodegenerative disease −such Alzheimer's disease-aiming to discuss whether network science is changing the traditional concept of brain disease and how network topology knowledge could help in modeling resilience and vulnerability of diseases. Aim of this work is to open discussion on how network model could better describe brain architecture.

Original language	English
Pages (from-to)	292-300
Number of pages	9
Journal	Behavioural Brain Research
Volume	317
DOIs	https://doi.org/10.1016/j.bbr.2016.09.057
Publication status	Published - Jan 15 2017

Keywords

Connectome
EEG
Functional connectivity
Graph theory
Resting state networks

ASJC Scopus subject areas

Behavioral Neuroscience

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10.1016/j.bbr.2016.09.057

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abstract = "Graph theory applications had spread widely in understanding how human cognitive functions are linked to dynamics of neuronal network structure, providing a conceptual frame that can reduce the analytical brain complexity. This review summarizes methodological advances in this field. Electroencephalographic functional network studies in pathophysiological aging will be presented, focusing on neurodegenerative disease −such Alzheimer's disease-aiming to discuss whether network science is changing the traditional concept of brain disease and how network topology knowledge could help in modeling resilience and vulnerability of diseases. Aim of this work is to open discussion on how network model could better describe brain architecture.",

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author = "Francesca Miraglia and Fabrizio Vecchio and Rossini, {Paolo Maria}",

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AU - Vecchio, Fabrizio

AU - Rossini, Paolo Maria

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N2 - Graph theory applications had spread widely in understanding how human cognitive functions are linked to dynamics of neuronal network structure, providing a conceptual frame that can reduce the analytical brain complexity. This review summarizes methodological advances in this field. Electroencephalographic functional network studies in pathophysiological aging will be presented, focusing on neurodegenerative disease −such Alzheimer's disease-aiming to discuss whether network science is changing the traditional concept of brain disease and how network topology knowledge could help in modeling resilience and vulnerability of diseases. Aim of this work is to open discussion on how network model could better describe brain architecture.

AB - Graph theory applications had spread widely in understanding how human cognitive functions are linked to dynamics of neuronal network structure, providing a conceptual frame that can reduce the analytical brain complexity. This review summarizes methodological advances in this field. Electroencephalographic functional network studies in pathophysiological aging will be presented, focusing on neurodegenerative disease −such Alzheimer's disease-aiming to discuss whether network science is changing the traditional concept of brain disease and how network topology knowledge could help in modeling resilience and vulnerability of diseases. Aim of this work is to open discussion on how network model could better describe brain architecture.

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KW - EEG

KW - Functional connectivity

KW - Graph theory

KW - Resting state networks

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Searching for signs of aging and dementia in EEG through network analysis

Abstract

Keywords

ASJC Scopus subject areas

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