Leveraging network analysis to support experts in their analyses of subjects with MCI and AD

Paolo Lo Giudice, Nadia Mammone, Francesco Carlo Morabito, Rocco Giuseppe Pizzimenti, Domenico Ursino, Luca Virgili

Research output: Contribution to journalArticle

Abstract

In this paper, we propose a network analysis–based approach to help experts in their analyses of subjects with mild cognitive impairment (hereafter, MCI) and Alzheimer’s disease (hereafter, AD) and to investigate the evolution of these subjects over time. The inputs of our approach are the electroencephalograms (hereafter, EEGs) of the patients to analyze, performed at a certain time and, again, 3 months later. Given an EEG of a subject, our approach constructs a network with nodes that represent the electrodes and edges that denote connections between electrodes. Then, it applies several network-based techniques allowing the investigation of subjects with MCI and AD and the analysis of their evolution over time. (i) A connection coefficient, supporting experts to distinguish patients with MCI from patients with AD; (ii) A conversion coefficient, supporting experts to verify if a subject with MCI is converting to AD; (iii) Some network motifs, i.e., network patterns very frequent in one kind of patient and absent, or very rare, in the other. Patients with AD, just by the very nature of their condition, cannot be forced to stay motionless while undergoing examinations for a long time. EEG is a non-invasive examination that can be easily done on them. Since AD and MCI, if prodromal to AD, are associated with a loss of cortical connections, the adoption of network analysis appears suitable to investigate the effects of the progression of the disease on EEG. This paper confirms the suitability of this idea [Figure not available: see fulltext.].

Original languageEnglish
Pages (from-to)1961-1983
Number of pages23
JournalMedical and Biological Engineering and Computing
Volume57
Issue number9
DOIs
Publication statusPublished - Sep 1 2019

Keywords

  • Alzheimer’s disease
  • Clique networks
  • Cliques
  • Colored networks
  • Connection coefficient
  • Conversion coefficient
  • Electroencephalograms
  • Mild cognitive impairment
  • Network analysis
  • Network motifs

ASJC Scopus subject areas

  • Biomedical Engineering
  • Computer Science Applications

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