Abstract

Theoretical consideration predicts that the alteration of local and shared information in the brain is a key element in the mechanism of anesthetic-induced unconsciousness. Ordinal pattern analysis, such as permutation entropy (PE) and symbolic mutual information (SMI), have been successful in quantifying local and shared information in neurophysiological data; however, they have been rarely applied to altered states of consciousness, especially to data obtained with functional magnetic resonance imaging (fMRI). PE and SMI analysis, together with the superb spatial resolution of fMRI recording, enables us to explore the local information of specific brain areas, the shared information between the areas, and the relationship between the two. Given the spatially divergent action of anesthetics on regional brain activity, we hypothesized that anesthesia would differentially influence entropy (PE) and shared information (SMI) across various brain areas, which may represent fundamental, mechanistic indicators of loss of consciousness. FMRI data were collected from 15 healthy participants during four states: wakefulness (W), light (conscious) sedation (L), deep (unconscious) sedation (D), and recovery (R). Sedation was produced by the common, clinically used anesthetic, propofol. Firstly, we found that that global PE decreased from W to D, and increased from D to R. The PE was differentially affected across the brain areas; specifically, the PE in the subcortical network was reduced more than in the cortical networks. Secondly, SMI was also differentially affected in different areas, as revealed by the reconfiguration of its spatial pattern (topographic structure). The topographic structures of SMI in the conscious states W, L, and R were distinctively different from that of the unconscious state D. Thirdly, PE and SMI were positively correlated in W, L, and R, whereas this correlation was disrupted in D. And lastly, PE changes occurred preferentially in highly connected hub regions. These findings advance our understanding of brain dynamics and information exchange, emphasizing the importance of topographic structure and the relationship of local and shared information in anesthetic-induced unconsciousness.

Highlights

  • The alteration of temporal dynamics in the brain is thought to be a key element in the mechanism of anesthetic-induced unconsciousness

  • Permutation entropy (PE) has been successfully applied to quantify local information derived from electroencephalographic signals (EEG), due to its robustness to artifacts, invariance with respect to nonlinear monotonous transformations, computational efficiency, and the minimal requirement for the pre-processing of EEG signals [3,4]

  • Local information in the 226 brain areas was measured by permutation entropy (PE), which depends on the temporal dynamics of each region (Figure 1A)

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Summary

Introduction

The alteration of temporal dynamics in the brain is thought to be a key element in the mechanism of anesthetic-induced unconsciousness. The anesthetic, propofol, causes regular and stereotypic dynamics [1,2], along with loss of consciousness. In the past, these changes were identified by using entropy or complexity measures. The PE of the EEG captures the progressive increase of regularity in close correlation with the level of consciousness under sedation [1,5,6]. It provides reasonable pharmacokinetic-pharmacodynamic models to predict the drug concentration and its effects [4,7]

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