Corrections to "Identification of the General Anesthesia Induced Loss of Consciousness by Cross Fuzzy Entropy-Based Brain Network"

In the above article [1] , to track the loss of consciousness (LOC) induced by general anesthesia (GA), we first developed the multi-channel cross fuzzy entropy method to construct the time- varying networks, whose temporal fluctuations were then explored and quantitatively evaluated. Since time-var...

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Bibliographic Details
Published in:IEEE transactions on neural systems and rehabilitation engineering 2022, Vol.30, p.2970-2970
Main Authors: Li, Fali, Li, Yuqin, Zheng, Hui, Jiang, Lin, Gao, Dongrui, Li, Cunbo, Peng, Yueheng, Cao, Zehong, Zhang, Yangsong, Yao, Dezhong, Xu, Tao, Yuan, Ti-fei, Xu, Peng
Format: Article
Language:English
Subjects:
Anesthesia
Coherence
Entropy
Fluctuations
Network topology
Time-varying systems
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Summary:In the above article [1] , to track the loss of consciousness (LOC) induced by general anesthesia (GA), we first developed the multi-channel cross fuzzy entropy method to construct the time- varying networks, whose temporal fluctuations were then explored and quantitatively evaluated. Since time-varying network topologies were found to fluctuate from long-range frontal-occipital to short-range prefrontal-frontal connectivity during the LOC period, a new parameter, i.e., the long-range connectivity (LRC) that measured the number of frontal-occipital connectivity, was accordingly calculated and then investigated between the coherence (COH) and cross fuzzy entropy (C-FuzzyEn) approaches, as displayed in Fig. 1 . The distinct time-varying fluctuations of both approaches were indeed found within this period, where only C-FuzzyEn effectively captured the consciousness fluctuation induced by the GA.
ISSN:1534-4320
1558-0210
DOI:10.1109/TNSRE.2022.3205527