Searching for signs of aging and dementia in EEG through network analysis.
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.
Brain Connectivity Laboratory, IRCCS San Raffaele Pisana, Rome, Italy; Institute of Neurology, Dept. Geriatrics, Neuroscience & Orthopedics, Catholic University, Policlinic A. Gemelli Rome, Italy. Electronic address: fra.miraglia@gmail.com.
Francesca
F
Miraglia
Brain Connectivity Laboratory, IRCCS San Raffaele Pisana, Rome, Italy.
Fabrizio
F
Vecchio
Brain Connectivity Laboratory, IRCCS San Raffaele Pisana, Rome, Italy; Institute of Neurology, Dept. Geriatrics, Neuroscience & Orthopedics, Catholic University, Policlinic A. Gemelli Rome, Italy.
Paolo Maria
PM
Rossini
D000375:Aging / Q000502:physiology*; D001931:Brain Mapping; D003704:Dementia / Q000503:physiopathology*; D004569:Electroencephalography; D006801:Humans; D009415:Nerve Net; D009483:Neuropsychological Tests
Connectome; EEG; Functional connectivity; Graph theory; Resting state networks