Functional connectivity in EEG resting-state is not stable but fluctuates considerably. The aim of this study was to investigate how efficient information flows through a network, i.e. how resting-state EEG networks are organized and whether this organization it also subject to fluctuations. Differences of the network organization (small-worldness), degree of clustered connectivity, and path length as an indicator of how information is integrated into the network across time was compared between theta, alpha and beta bands. We show robust differences in network organization (small-worldness) between frequency bands. Fluctuations in network organization were larger in the theta, compared to the alpha and beta frequency. Variation in network organization and not the frequency of fluctuations differs between frequency bands. Furthermore, the degree of clustered connectivity and its modulation across time is the same across frequency bands, but the path length revealed the same modulatory pattern as the small-world metric. It is therefore the interplay of local processing efficiency and global information processing efficiency in the brain that fluctuates in a frequency-specific way. Properties of how information can be integrated is subject to fluctuations in a frequency-specific way in the resting-state. The possible relevance of these resting-state EEG properties is discussed including its clinical relevance.

脑电静止状态下的功能连通性不稳定，但波动很大。这项研究的目的是调查有效信息如何通过网络流动，即静止状态EEG网络如何组织以及该组织是否也受到波动的影响。比较了theta，alpha和beta频段之间网络组织的差异（小世界），集群连接程度以及路径长度的差异，这些指标表明信息如何跨时间集成到网络中。我们显示了频段之间网络组织（小型世界）的强大差异。与alpha和beta频率相比，theta中网络组织的波动更大。网络组织的变化而不是波动频率在频带之间有所不同。此外，集群连通性的程度及其跨时间的调制在各个频带上是相同的，但是路径长度显示出与小世界度量标准相同的调制模式。因此，大脑中局部处理效率和全局信息处理效率之间的相互作用以特定于频率的方式波动。在静止状态下，如何集成信息的属性会以特定于频率的方式波动。讨论了这些静止状态脑电图特性的可能相关性，包括其临床相关性。因此，大脑中局部处理效率和全局信息处理效率之间的相互作用以特定于频率的方式波动。在静止状态下，如何集成信息的属性会以特定于频率的方式波动。讨论了这些静止状态脑电图特性的可能相关性，包括其临床相关性。因此，大脑中局部处理效率和全局信息处理效率之间的相互作用以特定于频率的方式波动。在静止状态下，如何集成信息的属性会以特定于频率的方式波动。讨论了这些静止状态脑电图特性的可能相关性，包括其临床相关性。