Resting state functional connectivity demonstrates increased segregation in bilateral temporal lobe epilepsy.

Area of Science:

• Neuroscience
• Network Science
• Epilepsy Research

Background:

• Temporal lobe epilepsy (TLE) is the most common focal epilepsy.
• Bilateral TLE (BiTLE) is an increasingly recognized subset characterized by independent seizures in both temporal lobes.
• Understanding the brain network differences in BiTLE is crucial for diagnosis and treatment.

Purpose of the Study:

• To investigate the interictal whole-brain network characteristics of bilateral TLE (BiTLE) using network neuroscience.
• To compare the functional brain networks of BiTLE patients with those of unilateral TLE (UTLE) patients.

Main Methods:

• Utilized a multicenter resting-state functional MRI (rs-fMRI) dataset.
• Constructed and analyzed whole-brain functional networks using network theory metrics (global efficiency, participation coefficient, modularity).
• Derived an "integration-segregation axis" using principal component analysis (PCA) on network metrics.

Main Results:

• BiTLE patients exhibited decreased global efficiency and participation coefficient compared to UTLE patients.
• BiTLE showed increased modularity, indicating a larger number of smaller communities.
• Network properties differentiated BiTLE from UTLE along the integration-segregation axis, with similar patterns observed in poor-outcome UTLE.

Conclusions:

• Increased interictal whole-brain network segregation is a specific marker for BiTLE.
• rs-fMRI derived network segregation may aid in non-invasive identification of BiTLE patients.
• These findings could inform pre-surgical evaluation and treatment strategies for TLE.