AUTHOR=Tang Fuqiu , Li Lan , Peng Dechang , Yu Jingjing , Xin Huizhen , Tang Xuan , Li Kunyao , Zeng Yaping , Xie Wei , Li Haijun 

TITLE=Abnormal static and dynamic functional network connectivity in stable chronic obstructive pulmonary disease

JOURNAL=Frontiers in Aging Neuroscience

VOLUME=Volume 14 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/aging-neuroscience/articles/10.3389/fnagi.2022.1009232

DOI=10.3389/fnagi.2022.1009232

ISSN=1663-4365

ABSTRACT=Objective: Many studies have explored the neural mechanisms of cognitive impairment in chronic obstructive pulmonary disease (COPD) patients using the functional MRI. However, the dynamic properties of brain functional networks are still unclear. The purpose of this study was to explore the changes in dynamic functional network attributes and their relationship with cognitive impairment in stable COPD patients. 
Materials and Methods: The resting-state functional MRI and cognitive assessments were performed on 19 stable COPD patients and 19 age-, sex-, and education-matched healthy controls (HCs). We conducted the independent component analysis (ICA) method on the resting-state fMRI data, and obtained seven resting-state networks (RSNs). After that, the static and dynamic functional network connectivity (sFNC and dFNC) were respectively constructed, and the differences of functional connectivity were compared between COPD patients and the HC groups. In addition, the correlation between dynamic functional network attributes and cognitive assessments was analyzed in COPD patients. 
Results: Compared to HCs, there were significant differences in sFNC among COPD patients between and within networks. COPD patients showed significantly longer mean dwell time and higher fractional windows in weaker connectivity State I than HCs. Besides, in comparison to HCs, COPD patients had more extensive functional connectivity abnormalities in weaker connectivity state I and state IV, and less abnormal functional connectivity in relatively stronger connectivity state II and state III, which were mainly located in the default mode network, executive control network, and visual network. In addition, the dFNC properties including mean dwell time and fractional windows are significantly correlated with some essential clinical indicators such as FEV1, FEV1/FVC and c-reactive protein in COPD patients.
Conclusion: These findings highlight the differences in static and dynamic functional connectivity in patients with COPD, which may serve as an important biomarker of cognitive performance. And this also provides a new perspective for understanding the cognitive neural mechanisms of COPD.