Alterations in static and dynamic functional network connectivity in chronic low back pain: a resting-state network...

Area of Science:

• Neuroscience
• Medical Imaging
• Pain Research

Background:

• Low back pain (LBP) is a common condition impacting sensory, cognitive, and emotional processing.
• Previous studies show brain abnormalities in LBP, but large-scale static and dynamic functional network connectivity (FNC) changes are unclear.

Purpose of the Study:

• To investigate static and dynamic large-scale FNC alterations in chronic low back pain (cLBP) patients.
• To compare brain network connectivity between cLBP patients and healthy controls.
• To explore potential machine learning applications for distinguishing cLBP.

Main Methods:

• Resting-state functional MRI (fMRI) was used for 41 cLBP patients and 42 healthy controls.
• Independent Component Analysis (ICA) extracted resting-state networks.
• Static and dynamic FNC, including temporal metrics, were analyzed and compared between groups.

Main Results:

• Reduced intra-network connectivity in the Default Mode Network (DMN), Dorsal Attention Network (DAN), and Executive Control Network (ECN) was observed in cLBP patients.
• Significant differences in static and dynamic FNC were found between cLBP patients and controls.
• Altered fraction time and mean dwell time in dynamic network connectivity were noted in cLBP patients.

Conclusions:

• Chronic low back pain is associated with significant alterations in both static and dynamic large-scale brain network connectivity.
• These findings offer insights into the neural mechanisms underlying altered brain function and pain perception in cLBP.
• The study highlights the complex neurobiological impact of chronic pain on brain networks.