“Small World” architecture in brain connectivity and hippocampal volume in Alzheimer’s disease: a study via graph theory from EEG data

Cesare Colosimo, Fabrizio Vecchio, Francesca Miraglia, Francesca Piludu, Giuseppe Granata, Roberto Romanello, Valeria Onofrj, Paolo Maria Rossini, Massimo Caulo, Placido Bramanti

Risultato della ricerca: Contributo in rivistaArticolo in rivista

45 Citazioni (Scopus)

Abstract

Brain imaging plays an important role in the study of Alzheimer’s disease (AD), where atrophy has been found to occur in the hippocampal formation during the very early disease stages and to progress in parallel with the disease’s evolution. The aim of the present study was to evaluate a possible correlation between “Small World” characteristics of the brain connectivity architecture—as extracted from EEG recordings—and hippocampal volume in AD patients. A dataset of 144 subjects, including 110 AD (MMSE 21.3) and 34 healthy Nold (MMSE 29.8) individuals, was evaluated. Weighted and undirected networks were built by the eLORETA solutions of the cortical sources’ activities moving from EEG recordings. The evaluation of the hippocampal volume was carried out on a subgroup of 60 AD patients who received a high-resolution T1-weighted sequence and underwent processing for surface-based cortex reconstruction and volumetric segmentation using the Freesurfer image analysis software. Results showed that, quantitatively, more correlation was observed in the right hemisphere, but the same trend was seen in both hemispheres. Alpha band connectivity was negatively correlated, while slow (delta) and fast-frequency (beta, gamma) bands positively correlated with hippocampal volume. Namely, the larger the hippocampal volume, the lower the alpha and the higher the delta, beta, and gamma Small World characteristics of connectivity. Accordingly, the Small World connectivity pattern could represent a functional counterpart of structural hippocampal atrophying and related-network disconnection.
Lingua originaleEnglish
pagine (da-a)473-485
Numero di pagine13
RivistaBrain Imaging and Behavior
Volume11
DOI
Stato di pubblicazionePubblicato - 2017

Keywords

  • Alzheimer
  • Behavioral Neuroscience
  • Cellular and Molecular Neuroscience
  • Cognitive Neuroscience
  • EEG
  • Functional connectivity
  • Graph theory
  • Hippocampus
  • MRI
  • Neurology
  • Neurology (clinical)
  • Psychiatry and Mental Health
  • Radiology, Nuclear Medicine and Imaging
  • eLORETA

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