基于失匹配负波的大脑功能性网络分析

Brain functional network analysis based on mismatch negativity

根据正常人与听力损伤患者的失匹配负波(MMN)数据建立大脑功能性网络,计算该大脑功能性网络的复杂网络统计特性,发现所建立的功能性网络相对于随机网络具有类似无标度特性,而且具有高聚类系数、小特征路径长度的小世界网络特性;另外,还计算了功能性网络的平均度和网络结构熵,结果发现正常人的功能性网络的平均度、聚类系数、结构熵等参数均高于听力损伤患者的相应参数,提示了听力损伤后脑功能网络连接减弱可能是声源分辨能力下降的中枢表现,同时也反映了平均度、聚类系数、结构熵等功能性网络参数可作为反应听力损伤后声源分辨能力下降的诊断标志。

It establishes a functional brain network according to the Mismatch Negative(MMN)wave data of normal peopleand patients with hearing impairment. With calculated the complex networks statistical characteristics of the functionalbrain network, it finds that the established functional brain network has similar no scaling properties with respect to therandom network, but also has high clustering coefficient, small characteristic path lengths of small world network characteristics.In addition, the average degree of functional network and network structure entropy are calculated. The resultsshow that the average degree, clustering coefficient and structure entropy of the functional network are higher than thoseof the patients with hearing impairment. It indicates the reduction of functional connectivity after hearing loss may contributeto the decreased spatial discrimination. The functional network parameters of average degree, clustering coefficient andnetwork structure entropy may be considered as the central markers with reflecting the capability of spatial discrimination.