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Functional brain connectivity in Alzheimer’s disease: An EEG study based on permutation disalignment index

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  • Yu, Haitao
  • Lei, Xinyu
  • Song, Zhenxi
  • Wang, Jiang
  • Wei, Xile
  • Yu, Baoqi

Abstract

Alzheimer’s disease (AD) is commonly associated with abnormally functional connectivity of the brain. In this study, we investigated functional brain connectivity of the patients with AD based on electroencephalography (EEG) recordings. Permutation disalignment index (PDI), a novel nonlinear, amplitude independent metric which robust to noise, was used to estimate the coupling between each pair-wise EEG signals. It is found that the value of PDI is inversely correlated with the strength of functional connectivity, which is weakened in AD brain compared with the controls. Furthermore, the strength of functional connectivity declined with the increase of the relative distance of electrodes for both AD and control groups, but the correlation was weakened in the former. Graph theory was further applied to study the alteration of functional brain networks in AD and the obtained results showed that the functional brain network is more homogenous in AD subjects. We also explored the topological properties from both global and local brain areas and found that small-world efficiency of AD networks is largely declined, which may be attributed to the disconnection between brain areas.

Suggested Citation

  • Yu, Haitao & Lei, Xinyu & Song, Zhenxi & Wang, Jiang & Wei, Xile & Yu, Baoqi, 2018. "Functional brain connectivity in Alzheimer’s disease: An EEG study based on permutation disalignment index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1093-1103.
    • Handle: RePEc:eee:phsmap:v:506:y:2018:i:c:p:1093-1103
    DOI: 10.1016/j.physa.2018.05.009
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    References listed on IDEAS

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    1. Amir Joudaki & Niloufar Salehi & Mahdi Jalili & Maria G Knyazeva, 2012. "EEG-Based Functional Brain Networks: Does the Network Size Matter?," PLOS ONE, Public Library of Science, vol. 7(4), pages 1-9, April.
    2. Wang, Jiang & Yang, Chen & Wang, Ruofan & Yu, Haitao & Cao, Yibin & Liu, Jing, 2016. "Functional brain networks in Alzheimer’s disease: EEG analysis based on limited penetrable visibility graph and phase space method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 174-187.
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