EEG brain network variability is correlated with other pathophysiological indicators of critical patients in neurology intensive care unit

Chunli Chen; Zhaojin Chen; Meiling Hu; Sha Zhou; Shiyun Xu; Guan Zhou; Jixuan Zhou; Yuqin Li; Baodan Chen; Dezhong Yao; Fali Li; Yizhou Liu; Simeng Su; Peng Xu; Xuntai Ma

Brain Research Bulletin (Feb 2024)

EEG brain network variability is correlated with other pathophysiological indicators of critical patients in neurology intensive care unit

Chunli Chen,
Zhaojin Chen,
Meiling Hu,
Sha Zhou,
Shiyun Xu,
Guan Zhou,
Jixuan Zhou,
Yuqin Li,
Baodan Chen,
Dezhong Yao,
Fali Li,
Yizhou Liu,
Simeng Su,
Peng Xu,
Xuntai Ma

Affiliations

Chunli Chen: The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China; School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China
Zhaojin Chen: The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China; School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China
Meiling Hu: Clinical Medical College of Chengdu Medical College, Chengdu 610500, People’s Republic of China; The First Affiliated Hospital of Chengdu Medical College, Chengdu 610599, People’s Republic of China
Sha Zhou: Clinical Medical College of Chengdu Medical College, Chengdu 610500, People’s Republic of China; The First Affiliated Hospital of Chengdu Medical College, Chengdu 610599, People’s Republic of China
Shiyun Xu: The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China; School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China
Guan Zhou: The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China; School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China
Jixuan Zhou: The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China; School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China
Yuqin Li: The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China; School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China
Baodan Chen: The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China; School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China
Dezhong Yao: The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China; School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China
Fali Li: The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China; School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China
Yizhou Liu: Clinical Medical College of Chengdu Medical College, Chengdu 610500, People’s Republic of China; The First Affiliated Hospital of Chengdu Medical College, Chengdu 610599, People’s Republic of China
Simeng Su: Clinical Medical College of Chengdu Medical College, Chengdu 610500, People’s Republic of China; The First Affiliated Hospital of Chengdu Medical College, Chengdu 610599, People’s Republic of China
Peng Xu: The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China; School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China; Corresponding author at: The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People’s Republic of China.
Xuntai Ma: Clinical Medical College of Chengdu Medical College, Chengdu 610500, People’s Republic of China; The First Affiliated Hospital of Chengdu Medical College, Chengdu 610599, People’s Republic of China; Corresponding author at: Clinical Medical College of Chengdu Medical College, Chengdu 610500, People’s Republic of China.

Journal volume & issue: Vol. 207
p. 110881

Abstract

Read online

Continuous electroencephalogram (cEEG) plays a crucial role in monitoring and postoperative evaluation of critical patients with extensive EEG abnormalities. Recently, the temporal variability of dynamic resting-state functional connectivity has emerged as a novel approach to understanding the pathophysiological mechanisms underlying diseases. However, little is known about the underlying temporal variability of functional connections in critical patients admitted to neurology intensive care unit (NICU). Furthermore, considering the emerging field of network physiology that emphasizes the integrated nature of human organisms, we hypothesize that this temporal variability in brain activity may be potentially linked to other physiological functions. Therefore, this study aimed to investigate network variability using fuzzy entropy in 24-hour dynamic resting-state networks of critical patients in NICU, with an emphasis on exploring spatial topology changes over time. Our findings revealed both atypical flexible and robust architectures in critical patients. Specifically, the former exhibited denser functional connectivity across the left frontal and left parietal lobes, while the latter showed predominantly short-range connections within anterior regions. These patterns of network variability deviating from normality may underlie the altered network integrity leading to loss of consciousness and cognitive impairment observed in these patients. Additionally, we explored changes in 24-hour network properties and found simultaneous decreases in brain efficiency, heart rate, and blood pressure between approximately 1 pm and 5 pm. Moreover, we observed a close relationship between temporal variability of resting-state network properties and other physiological indicators including heart rate as well as liver and kidney function. These findings suggest that the application of a temporal variability-based cEEG analysis method offers valuable insights into underlying pathophysiological mechanisms of critical patients in NICU, and may present novel avenues for their condition monitoring, intervention, and treatment.

Published in Brain Research Bulletin

ISSN: 1873-2747 (Online)
Publisher: Elsevier
Country of publisher: United States
LCC subjects: Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry
Website: https://www.sciencedirect.com/journal/brain-research-bulletin

About the journal

Abstract

Keywords