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

Research output: Contribution to journalReview article

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 languageEnglish
Pages (from-to)292-300
Number of pages9
JournalBehavioural Brain Research
Volume317
DOIs
Publication statusPublished - Jan 15 2017

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Dementia
Electroencephalography
Brain
Brain Diseases
Neurodegenerative Diseases
Cognition
Alzheimer Disease

Keywords

  • Connectome
  • EEG
  • Functional connectivity
  • Graph theory
  • Resting state networks

ASJC Scopus subject areas

  • Behavioral Neuroscience

Cite this

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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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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 - Functional connectivity

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KW - Resting state networks

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