Emerging roles of network analysis for epilepsy

Area of Science:

• Neuroscience
• Network Science
• Biomedical Engineering

Background:

• Increasing interest in applying network science to electroencephalography (EEG) data.
• Focus on translational technologies for analyzing seizure networks at the 2018 American Epilepsy Society conference.
• Exploration of emerging tools for clinical applications in epilepsy care.

Purpose of the Study:

• To demonstrate practical applications of network tools in clinical care using EEG data.
• To highlight how network analysis can provide additional data for managing intractable epilepsy.
• To showcase advances in analyzing human EEG data with network science methodologies.

Main Methods:

• Utilizing functional connectivity analysis.
• Applying control theory principles.
• Employing graph theory for EEG data interpretation.

Main Results:

• Demonstration of practical examples of network tool utilization in clinical settings.
• Presentation of advances in analyzing human EEG data using network science.
• Evidence of potential to augment clinical interpretation of EEG signals.

Conclusions:

• Network science tools show significant potential for analyzing seizure networks.
• These methodologies can provide valuable supplementary data for patient care in intractable epilepsy.
• Advances in functional connectivity, control theory, and graph theory offer promising avenues for EEG signal interpretation.