Literature DB >> 27693849

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

Francesca Miraglia1, Fabrizio Vecchio2, Paolo Maria Rossini3.   

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.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Connectome; EEG; Functional connectivity; Graph theory; Resting state networks

Mesh:

Year:  2016        PMID: 27693849     DOI: 10.1016/j.bbr.2016.09.057

Source DB:  PubMed          Journal:  Behav Brain Res        ISSN: 0166-4328            Impact factor:   3.332


  16 in total

1.  Human brain networks: a graph theoretical analysis of cortical connectivity normative database from EEG data in healthy elderly subjects.

Authors:  Fabrizio Vecchio; Francesca Miraglia; Elda Judica; Maria Cotelli; Francesca Alù; Paolo Maria Rossini
Journal:  Geroscience       Date:  2020-03-13       Impact factor: 7.713

2.  Transcranial direct current stimulation generates a transient increase of small-world in brain connectivity: an EEG graph theoretical analysis.

Authors:  Fabrizio Vecchio; Riccardo Di Iorio; Francesca Miraglia; Giuseppe Granata; Roberto Romanello; Placido Bramanti; Paolo Maria Rossini
Journal:  Exp Brain Res       Date:  2018-02-13       Impact factor: 1.972

3.  Neuronavigated Magnetic Stimulation combined with cognitive training for Alzheimer's patients: an EEG graph study.

Authors:  Fabrizio Vecchio; Davide Quaranta; Francesca Miraglia; Chiara Pappalettera; Riccardo Di Iorio; Federica L'Abbate; Maria Cotelli; Camillo Marra; Paolo Maria Rossini
Journal:  Geroscience       Date:  2021-12-31       Impact factor: 7.713

4.  Analysis of complexity in the EEG activity of Parkinson's disease patients by means of approximate entropy.

Authors:  Chiara Pappalettera; Francesca Miraglia; Maria Cotelli; Paolo Maria Rossini; Fabrizio Vecchio
Journal:  Geroscience       Date:  2022-03-28       Impact factor: 7.581

5.  Time and frequency dependent changes in resting state EEG functional connectivity following lipopolysaccharide challenge in rats.

Authors:  Matthew A Albrecht; Chloe N Vaughn; Molly A Erickson; Sarah M Clark; Leonardo H Tonelli
Journal:  PLoS One       Date:  2018-11-12       Impact factor: 3.240

6.  Measuring Brain Complexity During Neural Motor Resonance.

Authors:  Brandon M Hager; Albert C Yang; Jennifer N Gutsell
Journal:  Front Neurosci       Date:  2018-10-30       Impact factor: 4.677

Review 7.  Connectome: Graph theory application in functional brain network architecture.

Authors:  Fabrizio Vecchio; Francesca Miraglia; Paolo Maria Rossini
Journal:  Clin Neurophysiol Pract       Date:  2017-10-24

8.  tDCS effects on brain network properties during physiological aging.

Authors:  Fabrizio Vecchio; Francesca Miraglia; Claudia Rodella; Francesca Alù; Carlo Miniussi; Paolo Maria Rossini; Maria Concetta Pellicciari
Journal:  Pflugers Arch       Date:  2020-07-04       Impact factor: 3.657

9.  The Impact of Age and Cognitive Reserve on Resting-State Brain Connectivity.

Authors:  Jessica I Fleck; Julia Kuti; Jeffrey Mercurio; Spencer Mullen; Katherine Austin; Olivia Pereira
Journal:  Front Aging Neurosci       Date:  2017-12-01       Impact factor: 5.750

10.  Loss of brain inter-frequency hubs in Alzheimer's disease.

Authors:  J Guillon; Y Attal; O Colliot; V La Corte; B Dubois; D Schwartz; M Chavez; F De Vico Fallani
Journal:  Sci Rep       Date:  2017-09-07       Impact factor: 4.379

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