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Functional brain networks in parkinson's disease

Akbari, S ; Sharif University of Technology | 2018

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  1. Type of Document: Article
  2. DOI: 10.1109/ICBME.2017.8430243
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2018
  4. Abstract:
  5. Parkinson's disease (PD) is the second most common and progressive neurological disorder. Parkinson's signs are caused by dysfunction in PD patient's brain network. Newly, resting state functional magnetic resonance imaging has been utilized to assess the altered functional connectivity in PD patients. In this study, we investigated the properties of the brain network topology in 19 PD patients compared to 17 normal healthy group by means of graph theory. In addition, we used four different graph formation methods to explore linear and nonlinear relationships between fMRI signals. Each correlation measure created a weighted graph for each subject. Different graph characteristics have been extracted from the weighted graphs. Finally, we discovered between groups changes by nonparametric tests such as Mann-Whitney u-test and t-test. Based on our results, PD patients exhibited a marked reduction in centralization, a global measure, compared to healthy normal group. Furthermore, we explored alterations of brain network in terms of nodal-based properties. The obtained evaluations on topological properties suggest that Parkinson made alterations to the brain functional network. © 2017 IEEE
  6. Keywords:
  7. Brain network ; Graph formation ; Parkinson's disease ; Biomedical engineering ; Biophysics ; Graphic methods ; Group theory ; Magnetic resonance imaging ; Neurodegenerative diseases ; Signal systems ; Brain functional networks ; Brain networks ; fMRJ ; Functional connectivity ; Non-linear relationships ; Resting-state functional magnetic resonance imaging ; Graph theory
  8. Source: 24th Iranian Conference on Biomedical Engineering and 2017 2nd International Iranian Conference on Biomedical Engineering, ICBME 2017, 30 November 2017 through 1 December 2017 ; 2018 ; 9781538636091 (ISBN)
  9. URL: https://www.sciencedirect.com/science/article/pii/S1353802001000220