title: Brain network evolution after stroke based on computational experiments.
abstract: Stroke is a frequently-occurring disease threatening the human nervous system. As a serious debilitation affecting a large-scale, hierarchical, and vastly complex electrochemical system, stroke remains relatively misunderstood. Rehabilitation mechanisms and means have suffered from this lack of systematic understanding. Here we propose an evolution model to simulate the dynamic actual evolvement process of functional brain networks computationally in an effort to address current shortcomings in the state of the field. According to simulation results, we conclude that the brain networks of patients following acute stroke were characterized by lower small worldness and lower quantity of long-distance connections compared with the healthy condition. Moreover, distance penalization may be used to describe the general mechanism of brain network evolution in the acute period after stroke.
authors.affiliation: Image Processing and Intelligent Control Key Laboratory of Education Ministry of China, Wuhan, P. R. China ; Department of Intelligent Science and Technology, College of Automation, Huazhong University of Science and Technology, Wuhan, P. R. China.
authors.forename: Wei
authors.initials: W
authors.lastname: Li
authors.affiliation: Image Processing and Intelligent Control Key Laboratory of Education Ministry of China, Wuhan, P. R. China ; Department of Intelligent Science and Technology, College of Automation, Huazhong University of Science and Technology, Wuhan, P. R. China.
authors.forename: Yue
authors.initials: Y
authors.lastname: Huang
authors.affiliation: Image Processing and Intelligent Control Key Laboratory of Education Ministry of China, Wuhan, P. R. China ; Department of Intelligent Science and Technology, College of Automation, Huazhong University of Science and Technology, Wuhan, P. R. China.
authors.forename: Yapeng
authors.initials: Y
authors.lastname: Li
authors.affiliation: Image Processing and Intelligent Control Key Laboratory of Education Ministry of China, Wuhan, P. R. China ; Department of Systems Science and Engineering, College of Automation, Huazhong University of Science and Technology, Wuhan, P. R. China.
authors.forename: Xi
authors.initials: X
authors.lastname: Chen
mesh_terms: D000328:Adult; D000368:Aged; D001921:Brain / Q000503:physiopathology*; D016022:Case-Control Studies; D003198:Computer Simulation; D003710:Demography; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D009415:Nerve Net / Q000503:physiopathology*; D020521:Stroke / Q000503:physiopathology*