Visual network alterations in brain functional connectivity in chronic low back pain: A resting state functional...

Area of Science:

• Neuroscience
• Medical Imaging
• Pain Research

Background:

• Chronic low back pain (cLBP) is linked to brain alterations.
• Understanding functional connectivity changes is crucial for cLBP research.

Purpose of the Study:

• Investigate resting-state functional connectivity (rsFC) in visual networks of cLBP patients.
• Assess machine learning feasibility for differentiating cLBP patients from controls based on rsFC.

Main Methods:

• Used resting-state BOLD fMRI scans on 90 cLBP patients and 74 healthy controls.
• Analyzed primary, dorsal, and ventral visual networks using independent component analysis.
• Applied support vector machine (SVM) for classification, validated on an independent cohort.

Main Results:

• Found significantly enhanced functional connectivity between the primary visual network and somatosensory/motor areas in cLBP patients.
• Observed a negative association between rsFC of the primary visual network and S1 with cLBP duration.
• Achieved 79.3% classification accuracy (74% in validation cohort) distinguishing cLBP from HCs using visual network rsFC.

Conclusions:

• Demonstrated significant alterations in visual network rsFC in cLBP patients.
• Hypothesize these changes represent adaptive mechanisms and cross-modal interactions.
• Suggests visual network involvement in cLBP pathophysiology and potential for novel diagnostic approaches.