Mapping Individualized Dual-Axis Network Topology in Focal Epilepsy: Divergent Alterations in System Integrity,...

Area of Science:

• Neuroscience
• Systems Neuroscience
• Computational Neuroscience

Background:

• Focal epilepsy is increasingly viewed as a disorder affecting distributed brain systems.
• Understanding patient-specific network alterations in epilepsy is crucial for clinical applications.
• Current methods for characterizing network organization in epilepsy have limitations.

Purpose of the Study:

• To develop and validate an individualized network-estimation framework to characterize system-level topological alterations in focal epilepsy.
• To identify clinically meaningful patient-specific network signatures.
• To investigate the relationship between network topology, cognition, and epilepsy clinical features.

Main Methods:

• Utilized resting-state functional MRI (fMRI) data from large cohorts of epilepsy patients and healthy controls.
• Introduced an overlap-permitting individualized network-estimation framework anchored to normative references.
• Derived two complementary system-level topological axes: network correspondence and k-hubness.

Main Results:

• Disruption in network correspondence was a shared endpoint across individuals, impacting cognition differently.
• K-hubness reconfigurations indicated lateralized and syndrome-dependent shifts in brain integration.
• These topological axes showed dissociable associations with neurocognitive deficits and epilepsy clinical features.

Conclusions:

• The derived network correspondence and k-hubness axes represent distinct topological phenotypes in focal epilepsy.
• These patient-level signatures offer reproducible insights into how seizures affect brain system organization and integration.
• The findings provide a foundation for understanding syndrome-specific and common effects of epilepsy on brain networks.