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Original Articles

Global and regional connectivity analysis of resting-state function MRI brain images using graph theory in Parkinson’s disease

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Pages 105-115 | Received 05 Mar 2019, Accepted 11 Feb 2020, Published online: 03 Mar 2020
 

Abstract

Objectives

Parkinson’s disease (PD) is the second most common neurodegenerative disorder which resists around 10 million people worldwide. It develops when nerve cells in a region of the brain that regulates movement become damaged; the symptoms usually begin gradually and become critical over time. In this study, we proposed to investigate the topological properties of functional brain networks within healthy controls (HCs) and PD patients. Also, we evaluated the gender difference among PD patients through graph theoretical approach.

Materials and Methods

The rs-fMRI (resting-state functional magnetic resonance imaging) data of fifty-one PD patients and healthy controls was applied to generate the brain functional connectome. The functional whole-brain connectome was constructed by thresholding partial correlation matrices of 160 regions from Dosenbach brain atlas. From the graph theory approach, global and nodal metrics were analysed, and we observed considerable changes in PD patients in comparison with healthy controls.

Results

Findings suggest that there is a significant difference in the topological characteristics of PD patients, and this was found to be evident in the default mode network (DMN) and occipital regions.

Conclusion

This study provides essential insights from network changes to the clinically relevant information for the PD progression.

Acknowledgment

The authors would like to express their sincere and deep-felt thanks to the Vellore Institute of Technology, Vellore for providing the necessary facilities that we required.

Disclosure statement

No potential conflict of interest was reported by the author(s).

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