Altered Brain Networks in Chronic Obstructive Pulmonary Disease: An Electroencephalography Analysis

Abstract

Background. Limited data are available regarding brain networks in patients with chronic obstructive pulmonary disease (COPD). Here, we investigated brain networks in COPD using graph theoretical analysis of electroencephalography data. Methods. Thirty-eight patients with COPD and 38 healthy controls underwent scalp electroencephalography. We calculated graph measures including average degree, characteristic path length, global efficiency, local efficiency, clustering coefficient, and modularity and compared them between patients and controls. Results. Average degree, global efficiency, local efficiency, and clustering coefficients were lower, while characteristic path length and modularity were higher in patients with COPD than in controls in the alpha band (P < .05). Significant differences in node degree and global node efficiency between controls and patients were mainly prominent in the medial parieto-central regions in the alpha band. Local efficiency and node clustering coefficients mainly differed in the occipito-parietal regions in the alpha band. We observed no differences in nodal measures in the delta, theta, beta, and gamma bands and no relationships between pulmonary function test parameters and global measures in any frequency bands. Conclusions. The thalamus generates alpha activity and is responsible for controlling respiratory activities to maintain oxygen delivery to tissues in response to chronic hypoxia. We thus speculate that our findings might be related to exposure to chronic hypoxia, implicated in the pathophysiological mechanisms underlying cognitive deficits in patients with COPD. Graph theoretical analysis of resting-state electroencephalography could be considered as a quantitative framework to understand functional networks in COPD.