Topological disintegration of resting state functional connectomes in coma

Area of Science:

• Neuroscience
• Network Science
• Computational Biology

Background:

• Graph theory is crucial for understanding brain network organization and identifying neural correlates of consciousness.
• Analyzing brain networks in patients with disorders of consciousness presents challenges due to arbitrary thresholding, risking spurious connections.

Purpose of the Study:

• To investigate functional brain network organization in coma patients using graph theory.
• To develop and apply a robust thresholding method for constructing functional connectomes in patients with disorders of consciousness.

Main Methods:

• Resting-state functional magnetic resonance imaging (fMRI) data from 25 coma patients and 22 healthy subjects were analyzed.
• A novel fixed-density thresholding method (10%) was established using healthy subjects' data and applied to patient groups.
• Graph theory metrics were used to compare the structural and functional connectivity of brain networks.

Main Results:

• Coma patients displayed a reduced number of significant brain connections compared to healthy controls.
• Approximately 50% of coma patients did not meet the established fixed-density threshold criteria.
• Patients with preserved global functional connectivity showed significant whole-brain network reorganization.

Conclusions:

• The findings underscore the need for careful consideration when constructing functional connectomes in patients with disorders of consciousness.
• The developed thresholding method offers improved comparability and reduces spurious connections in clinical populations.
• This research lays the groundwork for future studies on the clinical implications of altered brain network organization in disorders of consciousness.