Information Integration and Mesoscopic Cortical Connectivity during Propofol Anesthesia.

BACKGROUND: The neurophysiologic mechanisms of propofol-induced loss of consciousness have been studied in detail at the macro (scalp electroencephalogram) and micro (spiking or local field potential) scales. However, the changes in information integration and cortical connectivity during propofol anesthesia at the mesoscopic level (the cortical scale) are less clear. METHODS: The authors analyzed electrocorticogram data recorded from surgical patients during propofol-induced unconsciousness (n = 9). A new information measure, genuine permutation cross mutual information, was used to analyze how electrocorticogram cross-electrode coupling changed with electrode-distances in different brain areas (within the frontal, parietal, and temporal regions, as well as between the temporal and parietal regions). The changes in cortical networks during anesthesia-at nodal and global levels-were investigated using clustering coefficient, path length, and nodal efficiency measures. RESULTS: In all cortical regions, and in both wakeful and unconscious states (early and late), the genuine permutation cross mutual information and the percentage of genuine connections decreased with increasing distance, especially up to about 3 cm. The nodal cortical network metrics (the nodal clustering coefficients and nodal efficiency) decreased from wakefulness to unconscious state in the cortical regions we analyzed. In contrast, the global cortical network metrics slightly increased in the early unconscious state (the time span from loss of consciousness to 200 s after loss of consciousness), as compared with wakefulness (normalized average clustering coefficient: 1.05 ± 0.01 vs. 1.06 ± 0.03, P = 0.037; normalized average path length: 1.02 ± 0.01 vs. 1.04 ± 0.01, P = 0.021). CONCLUSIONS: The genuine permutation cross mutual information reflected propofol-induced coupling changes measured at a cortical scale. Loss of consciousness was associated with a redistribution of the pattern of information integration; losing efficient global information transmission capacity but increasing local functional segregation in the cortical network.