Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan 48109-5048, USA.
Anesthesiology. 2011 Apr;114(4):872-81. doi: 10.1097/ALN.0b013e31821102c9.
It is still unknown whether anesthetic state transitions are continuous or binary. Mathematical graph theory is one method by which to assess whether brain networks change gradually or abruptly upon anesthetic induction and emergence.
Twenty healthy males were anesthetized with an induction dose of propofol, with continuous measurement of 21-channel electroencephalogram at baseline, during anesthesia, and during recovery. From these electroencephalographic data a "genuine network" was reconstructed based on the surrogate data method. The effects of topologic structure and connection strength on information transfer through the network were measured independently across different states.
Loss of consciousness was consistently associated with a disruption of network topology. However, recovery of consciousness was associated with complex patterns of altered connection strength after the initial topologic structure had slowly recovered. In one group of subjects, there was a precipitous increase of connection strength that was associated with reduced variability of emergence time. Analysis of regional effects on brain networks demonstrated that the parietal network was significantly disrupted, whereas the frontal network was minimally affected.
By dissociating the effects of network structure and connection strength, both continuous and discrete elements of anesthetic state transitions were identified. The study also supports a critical role of parietal networks as a target of general anesthetics.
麻醉状态的转变是连续的还是二进制的，目前尚不清楚。数学图论是评估麻醉诱导和苏醒时大脑网络是否逐渐或突然变化的一种方法。
20 名健康男性接受异丙酚诱导麻醉，在基线、麻醉期间和恢复期间连续测量 21 通道脑电图。从这些脑电图数据中，基于替代数据方法重建了“真实网络”。独立测量了不同状态下拓扑结构和连接强度对网络中信息传递的影响。
意识丧失始终与网络拓扑结构的破坏有关。然而，意识的恢复与初始拓扑结构缓慢恢复后连接强度的复杂变化模式有关。在一组受试者中，连接强度急剧增加，与苏醒时间的变异性降低有关。对脑网络的区域效应分析表明，顶叶网络明显受到干扰，而额叶网络受影响最小。
通过分离网络结构和连接强度的影响，确定了麻醉状态转变的连续和离散元素。该研究还支持顶叶网络作为全身麻醉靶标的关键作用。
