Using network analysis to examine the connectivity between the brain regions in rs-fMRI data of FND patient and healthy participant : A single subject study

Abstract

Introduction: Functional neurological disorders (FND) is one of the most common causes of neuropathy, However, its cause continues to be mysterious. Understanding the underlying mechanisms of FND is crucial for treatment strategies. The study was conducted on brain images(rs-fMRI) taken from two volunteers (FND patient and healthy subject) who had the same characteristics. Method: We fitted Gaussian Graphical Models to a single subject data using a network approach. Results: Based on the results of the networks, the number of significant edges was more in the left hemisphere in the patient, but in the healthy person, the number of these non-zero edges was more in the right hemisphere. Both the networks related to the healthy person and the patient had high density. Therefore, it indicated that the regions considered by these 2 people were strongly related to each other. The results showed the existence of more links and positive relationships between the regions, most of which showed a strong relationship. Among these connections, there were also negative connections. The networks of the healthy participant with almost symmetrical structures and the patient with FND showed different characteristics, including asymmetry between the hemispheres. Conclusion: this study is the first to demonstrate that the brain regions of both FND patient and healthy participant can be conceptualized as networks. The findings of this study add to a growing body of literature that FND patient brain regions can be analyzed using network approaches.

Keywords

• FND disease
• graphical lasso
• rs-fMRI
• Network analysis
• Gaussian graphical model