Ranking Regions, Edges and Classifying Tasks in Functional Brain Graphs by Sub-Graph Entropy

• Published in: Scientific reports Vol. 9; no. 1; p. 7628
• Main Authors: Sen, Bhaskar, Chu, Shu-Hsien, Parhi, Keshab K.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 20.05.2019; Nature Publishing Group
• Subjects: 59/36; 631/114/1305; 631/114/2164; 631/114/2415; 631/378/116/1925; 639/166/987; Brain - physiology; Brain mapping; Classification; Connectome - methods; Correlation coefficient; Emotions - physiology; Entropy; Functional magnetic resonance imaging; Gambling; Humanities and Social Sciences; Humans; Magnetic Resonance Imaging - methods; multidisciplinary; Nerve Net - physiology; Neuroimaging; Nodes; Science; Science (multidisciplinary); Support Vector Machine; Time series

This paper considers analysis of human brain networks or graphs constructed from time-series collected from functional magnetic resonance imaging (fMRI). In the network of time-series, the nodes describe the regions and the edge weights correspond to the absolute values of correlation coefficients o...