Li Wei, Huang Yue, Li Yapeng, Chen Xi
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.
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.
PLoS One. 2013 Dec 20;8(12):e82845. doi: 10.1371/journal.pone.0082845. eCollection 2013.
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.
中风是一种常见的威胁人类神经系统的疾病。作为一种影响大规模、分层且极其复杂的电化学系统的严重衰弱病症，中风仍相对未被充分理解。康复机制和方法正因这种缺乏系统性的理解而受到影响。在此，我们提出一种演化模型，通过计算模拟功能性脑网络的动态实际演化过程，以解决该领域当前存在的不足。根据模拟结果，我们得出结论：与健康状态相比，急性中风患者的脑网络具有较小的小世界性和较少的长距离连接数量。此外，距离惩罚可能用于描述中风后急性期脑网络演化的一般机制。
