Multimodal, noninvasive seizure network mapping software: A novel tool for preoperative epilepsy evaluation

Area of Science:

• Neuroscience
• Medical Imaging
• Computational Biology

Background:

• Epilepsy surgery success rates are limited, with only two-thirds of patients achieving seizure freedom.
• Current preoperative evaluations lack detailed network analysis, despite its association with epilepsy.

Purpose of the Study:

• To develop a software algorithm for mapping individualized epilepsy brain networks.
• To combine noninvasive electroencephalography (EEG) source localization and resting-state functional magnetic resonance imaging (rsfMRI) for network mapping.

Main Methods:

• Acquired scalp EEG and rsfMRI data from healthy and epilepsy patient cases.
• Processed rsfMRI data to extract time-series functions and model global functional networks.
• Localized epileptic discharges using EEG source localization and co-registered with rsfMRI data.

Main Results:

• Demonstrated symmetrical global connectivity in a healthy control.
• Identified asymmetrical connectivity in a right temporal lobe epilepsy case, with reduced ipsilateral connectivity.
• Visualized white matter tracts connecting disparate cortical regions in epilepsy networks.

Conclusions:

• The algorithm effectively defines brain networks and highlights connectivity differences in epilepsy.
• This multimodal, noninvasive approach visualizes putative epilepsy networks and aids in localizing epileptogenic brain regions.
• The software tool offers a novel method for mapping cortico-cortical connections in epilepsy.