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

Area of Science:

• Neuroscience
• Medical Imaging
• Pulmonology

Background:

• Cognitive impairment is a common comorbidity in chronic obstructive pulmonary disease (COPD).
• While functional MRI studies have explored neural mechanisms, the dynamic properties of brain functional networks in COPD remain unclear.

Purpose of the Study:

• To investigate alterations in dynamic functional network attributes in stable COPD patients.
• To explore the relationship between these dynamic network changes and cognitive impairment.

Main Methods:

• Resting-state functional MRI and cognitive assessments were conducted on 19 stable COPD patients and 19 healthy controls (HC).
• Independent component analysis (ICA) was used to identify resting-state networks (RSNs).
• Static and dynamic functional network connectivity (sFNC and dFNC) were analyzed, comparing COPD patients and HC, and correlating dFNC with clinical indicators.

Main Results:

• COPD patients showed significant differences in sFNC compared to HC.
• Dynamic functional network analysis revealed altered states (longer mean dwell time, higher fractional windows in weaker states) in COPD patients.
• Abnormal functional connectivity patterns were observed in specific RSNs (default mode, executive control, visual networks) in COPD patients.
• dFNC properties correlated significantly with clinical indicators like FEV1, FEV1/FVC, and CRP in COPD patients.

Conclusions:

• Significant differences in static and dynamic functional network connectivity exist in COPD patients.
• These findings offer a novel perspective on the neural underpinnings of cognitive impairment in COPD.
• Dynamic functional network attributes show potential as neuroimaging biomarkers for cognitive performance in COPD.