Brain networks and dynamic network backbones for nine subjects and each anesthetic (cross-correlation network).

A unique network is a network with a distinctive connection structure in the given network time series. Network ensemble size is the number of unique network structures appearing in the data. The number of common backbones is the number of commonly found backbones across most subjects (>77%, 7/9 subjects in this study). maxP denotes the maximum occupation probability that the network backbones can have for the pooled data. minP denotes the minimum occupation probability that the network backbones can have. For example, minP(12) means the minimum occupation probability of the top 12 backbones. The minP(#) demonstrates how slowly the occupation probability was reduced as the number of network backbones considered increases. Note that in the anesthetized state the number of unique networks was reduced from baseline, indicating more frequent repetition of the same network and network backbone.