A Graph Theory based Pipeline for Intraoperative Resting-State fMRI Analysis

Motivation: Immediate changes in functional connectivity during brain surgery in epilepsy patients are worth investigating in order to improve surgical planning and prediction of surgical outcomes. Goal(s): We want to investigate changes in brain functionality during surgery using resting-state fMRI. Approach: We correlate the mean time series of cortical ROIs to compare functional connectivity differences between pre- and post-surgery scans for each patient and calculate global network measures for group comparisons. Results: Our approach enables visualization of functional connectivity before and after surgery, providing a valuable tool for investigating functional changes during the procedure. Impact: We demonstrated the feasibility of pre- and post-surgery data preprocessing, which enables intraoperative fMRI analysis using graph theory, allowing investigation of functional changes during brain surgery. This approach may lead to future improvements in neurosurgical outcomes.