Liu Huan, Li Hong, Wang Yulin, Lei Xu
Key Laboratory of Cognition and Personality (Ministry of Education) and School of Psychology, Southwest University, Chongqing, China.
J Sleep Res. 2014 Oct;23(5):554-63. doi: 10.1111/jsr.12147. Epub 2014 Mar 28.
Sleep deprivation has a variable impact on extrinsic activities during multiple cognitive tasks, especially on mood and emotion processing. There is also a trait-like individual vulnerability or compensatory effect in cognition. Previous studies have elucidated the altered functional connectivity after sleep deprivation. However, it remains unclear whether the small-world properties of resting-state network are sensitive to sleep deprivation. A small-world network is a type of graph that combines a high local connectivity as well as a few long-range connections, which ensures a higher information-processing efficiency at a low cost. The complex network of the brain can be described as a small-world network, in which a node is a brain region and an edge is present when there is a functional correlation between two nodes. Here, we investigated the topological properties of the human brain networks of 22 healthy subjects under sufficient sleep and sleep-deprived conditions. Specifically, small-worldness is utilized to quantify the small-world property, by comparing the clustering coefficient and path length of a given network to an equivalent random network with same degree distribution. After sufficient sleep, the brain networks showed the property of small-worldness. Compared with the resting state under sufficient sleep, the small-world property was significantly enhanced in the sleep deprivation condition, suggesting a possible compensatory adaptation of the human brain. Specifically, the altered measurements were correlated with the neuroticism of subjects, indicating that individuals with low-levels of neuroticism are more resilient to sleep deprivation.
睡眠剥夺对多项认知任务中的外在活动有不同影响，尤其是对情绪和情感处理。在认知方面也存在一种特质性的个体易感性或补偿效应。先前的研究已经阐明了睡眠剥夺后功能连接的改变。然而，静息态网络的小世界特性是否对睡眠剥夺敏感仍不清楚。小世界网络是一种图，它结合了高局部连接性以及少量长程连接，这确保了以低成本实现更高的信息处理效率。大脑的复杂网络可以被描述为一个小世界网络，其中一个节点是一个脑区，当两个节点之间存在功能相关性时就存在一条边。在这里，我们研究了22名健康受试者在充足睡眠和睡眠剥夺条件下的人脑网络的拓扑特性。具体而言，通过将给定网络的聚类系数和路径长度与具有相同度分布的等效随机网络进行比较，利用小世界特性来量化小世界属性。充足睡眠后，大脑网络呈现出小世界特性。与充足睡眠下的静息态相比，睡眠剥夺条件下小世界属性显著增强，这表明人脑可能存在一种补偿性适应。具体来说，测量值的改变与受试者的神经质有关，表明低神经质水平的个体对睡眠剥夺更具恢复力。
