Li Jianfu, Luo Cheng, Peng Yueheng, Xie Qiankun, Gong Jinnan, Dong Li, Lai Yongxiu, Li Hong, Yao Dezhong
Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
Key Laboratory of Cognition and Personality of Ministry of Education, Southwest University, Chongqing, China.
PLoS One. 2014 Aug 26;9(8):e105508. doi: 10.1371/journal.pone.0105508. eCollection 2014.
Musicians experience a large amount of information transfer and integration of complex sensory, motor, and auditory processes when training and playing musical instruments. Therefore, musicians are a useful model in which to investigate neural adaptations in the brain.
Here, based on diffusion-weighted imaging, probabilistic tractography was used to determine the architecture of white matter anatomical networks in musicians and non-musicians. Furthermore, the features of the white matter networks were analyzed using graph theory.
Small-world properties of the white matter network were observed in both groups. Compared with non-musicians, the musicians exhibited significantly increased connectivity strength in the left and right supplementary motor areas, the left calcarine fissure and surrounding cortex and the right caudate nucleus, as well as a significantly larger weighted clustering coefficient in the right olfactory cortex, the left medial superior frontal gyrus, the right gyrus rectus, the left lingual gyrus, the left supramarginal gyrus, and the right pallidum. Furthermore, there were differences in the node betweenness centrality in several regions. However, no significant differences in topological properties were observed at a global level.
We illustrated preliminary findings to extend the network level understanding of white matter plasticity in musicians who have had long-term musical training. These structural, network-based findings may indicate that musicians have enhanced information transmission efficiencies in local white matter networks that are related to musical training.
音乐家在训练和演奏乐器时会经历大量复杂的感觉、运动和听觉过程的信息传递与整合。因此,音乐家是研究大脑神经适应性的有用模型。
在此,基于扩散加权成像,使用概率纤维束成像来确定音乐家和非音乐家白质解剖网络的结构。此外,使用图论分析白质网络的特征。
两组均观察到白质网络的小世界特性。与非音乐家相比,音乐家在左右辅助运动区、左侧距状裂及其周围皮层以及右侧尾状核的连接强度显著增加,并且在右侧嗅觉皮层、左侧额上回内侧、右侧直回、左侧舌回、左侧缘上回和右侧苍白球的加权聚类系数显著更大。此外,几个区域的节点中介中心性存在差异。然而,在全局水平上未观察到拓扑特性的显著差异。
我们展示了初步研究结果,以扩展对经过长期音乐训练的音乐家白质可塑性的网络层面理解。这些基于网络的结构发现可能表明,音乐家在与音乐训练相关的局部白质网络中提高了信息传递效率。