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Network properties of healthy and Alzheimer brains

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  • Coninck, José C.P.
  • Ferrari, Fabiano A.S.
  • Reis, Adriane S.
  • Iarosz, Kelly C.
  • Caldas, Iberê L.
  • Batista, Antonio M.
  • Viana, Ricardo L.

Abstract

The application of graph theory in diffusion weighted resonance magnetic images have allowed the description of the brain as a complex network, often called structural network. For many years, the small-world properties of brain networks have been studied and reported. However, few studies have gone beyond of clustering and characteristic path length. In this work, we compare the structural connection network of a healthy brain and a brain affected by Alzheimer’s disease with artificial small-world networks. Based on statistical analysis, we demonstrate how artificial networks can be constructed using Newman–Watts procedure. The network quantifiers of both structural matrices are identified inside a probabilistic valley. Despite of similarities between structural connection matrices and artificial small-world networks, increased assortativity can be found in the Alzheimer brain. Due to limited experimental data, we cannot define a direct link between Alzheimer’s disease and assortativity. Nevertheless, we intend to call attention for an important network quantifier that has been neglected. Our results indicate that network quantifiers can be helpful to identify abnormalities in real structural connections, for instance Alzheimer’s disease that disrupts the communication among neurons. One of our main results is to show that the network indicators of the Alzheimer brain are almost identical with the small-world network, except the assortativity.

Suggested Citation

  • Coninck, José C.P. & Ferrari, Fabiano A.S. & Reis, Adriane S. & Iarosz, Kelly C. & Caldas, Iberê L. & Batista, Antonio M. & Viana, Ricardo L., 2020. "Network properties of healthy and Alzheimer brains," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
  • Handle: RePEc:eee:phsmap:v:547:y:2020:i:c:s0378437120302065
    DOI: 10.1016/j.physa.2020.124475
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    References listed on IDEAS

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    1. Ramon Ferrer i Cancho & Christiaan Janssen & Ricard V. Solé, 2001. "The Topology of Technology Graphs: Small World Patterns in Electronic Circuits," Working Papers 01-05-029, Santa Fe Institute.
    2. Liangming He & Duanwen Shi, 2008. "Synchronization In The Family Of Chaotic Small-World Networks," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 111-123.
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    Cited by:

    1. Hansen, Matheus & Protachevicz, Paulo R. & Iarosz, Kelly C. & Caldas, Iberê L. & Batista, Antonio M. & Macau, Elbert E.N., 2022. "Dynamics of uncoupled and coupled neurons under an external pulsed current," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    2. Qu, Lianghui & Du, Lin & Cao, Zilu & Hu, Haiwei & Deng, Zichen, 2021. "Pattern transition of neuronal networks induced by chemical autapses with random distribution," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    3. Reis, Adriane S. & Iarosz, Kelly C. & Ferrari, Fabiano A.S. & Caldas, Iberê L. & Batista, Antonio M. & Viana, Ricardo L., 2021. "Bursting synchronization in neuronal assemblies of scale-free networks," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).

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