Early MS Identification Using Non-linear Functional Connectivity and Graph-theoretic Measures of Cognitive Task-fMRI Data.

Journal: Basic and clinical neuroscience
Published Date: Nov 1, 2023

Abstract

INTRODUCTION: Functional neuroimaging has developed a fundamental ground for understanding the physical basis of the brain. Recent studies have extracted invaluable information from the underlying substrate of the brain. However, cognitive deficiency has insufficiently been assessed by researchers in multiple sclerosis (MS). Therefore, extracting the brain network differences among relapsing-remitting MS (RRMS) patients and healthy controls as biomarkers of cognitive task functional magnetic resonance imaging (fMRI) data and evaluating such biomarkers using machine learning were the aims of this study.

Authors

  • Farzad Azarmi
    Department of Biomedical Engineering and Medical Physics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Ahmad Shalbaf
    Department of Biomedical Engineering and Medical Physics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Seyedeh Naghmeh Miri Ashtiani
    Department of Biomedical Engineering, School of Electrical Engineering, Iran University of Science & Technology, Tehran, Iran.
  • Hamid Behnam
    Department of Biomedical Engineering, School of Electrical Engineering, Iran University of Science & Technology, Tehran, Iran.
  • Mohammad Reza Daliri
    Department of Biomedical Engineering, School of Electrical Engineering, Iran University of Science & Technology, Tehran, Iran.

Keywords

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