A Comparative Study of Correlation Methods in Functional Connectivity Analysis Using fMRI Data of Alzheimer’s Patients
محل انتشار: مجله فیزیک و مهندسی پزشکی، دوره: 13، شماره: 2
سال انتشار: 1402
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 51
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شناسه ملی سند علمی:
JR_JBPE-13-2_004
تاریخ نمایه سازی: 30 دی 1402
چکیده مقاله:
Background: Functional Magnetic Resonance Imaging (fMRI) is a non-invasive neuroimaging tool, used in brain function research and is also a low-frequency signal, showing brain activation by means of Oxygen consumption. Objective: One of the reliable methods in brain functional connectivity analysis is the correlation method. In correlation analysis, the relationship between two time-series has been investigated. In fMRI analysis, the Pearson correlation is used while there are other methods. This study aims to investigate the different correlation methods in functional connectivity analysis.Material and Methods: In this analytical research, based on fMRI signals of Alzheimer’s Disease (AD) and healthy individuals from the ADNI database, brain functional networks were generated using correlation techniques, including Pearson, Kendall, and Spearman. Then, the global and nodal measures were calculated in the whole brain and in the most important resting-state network called Default Mode Network (DMN). The statistical analysis was performed using non-parametric permutation test. Results: Results show that although in nodal analysis, the performance of correlation methods was almost similar, in global features, the Spearman and Kendall were better in distinguishing AD subjects. Note that, nodal analysis reveals that the functional connectivity of the posterior areas in the brain was more damaged because of AD in comparison to frontal areas. Moreover, the functional connectivity of the dominant hemisphere was disrupted more. Conclusion: Although the Pearson method has limitations in capturing non-linear relationships, it is the most prevalent method. To have a comprehensive analysis, investigating non-linear methods such as distance correlation is recommended.
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نویسندگان
Hessam Ahmadi
Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
Emad Fatemizadeh
School of Electrical Engineering, Sharif University of Technology, Tehran, Iran
Ali Motie Nasrabadi
Department of Biomedical Engineering, Shahed University, Tehran, Iran
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