Functional Connectivity Estimated from Intracranial EEG Predicts Surgical Outcome in Intractable Temporal Lobe Epilepsy

Abstract

This project aimed to determine if a correlation-based measure of functional connectivity can identify epileptogenic zones from intracranial EEG signals, as well as to investigate the prognostic significance of such a measure on seizure outcome following temporal lobe lobectomy. To this end, we retrospectively analyzed 23 adult patients with intractable temporal lobe epilepsy (TLE) who underwent an invasive stereo-EEG (SEEG) evaluation between January 2009 year and January 2012. A follow-up of at least one year was required. The primary outcome measure was complete seizure-freedom at last follow-up. Functional connectivity between two areas in the temporal lobe that were sampled by two SEEG electrode contacts was defined as Pearson’s correlation coefficient of interictal activity between those areas. SEEG signals were filtered between 5 and 50 Hz prior to computing this correlation. The mean and standard deviation of the off diagonal elements in the connectivity matrix were also calculated. Analysis of the mean and standard deviation of the functional connections for each patient reveals that 90% of the patients who had weak and homogenous connections were seizure free one year after temporal lobectomy, whereas 85% of the patients who had stronger and more heterogeneous connections within the temporal lobe had recurrence of seizures. This suggests that temporal lobectomy is ineffective in preventing seizure recurrence for patients in whom the temporal lobe is characterized by weakly connected, homogenous networks. This pilot study shows promising potential of a simple measure of functional brain connectivity to identify epileptogenicity and predict the outcome of epilepsy surgery.

Organization and control of epileptic circuits in temporal lobe epilepsy

“…When the strength of connectivity was measured in patients with TLE using functional connectivity of the stereo-EEG electrodes, patients with lower mean and standard deviation of connectivity strength had a significantly better outcome after temporal lobectomy (Antony et al, 2013). When the graph characteristics of intracranial EEG were analyzed, it turns out that the node with the highest “outdegree,” ie, highest number of outgoing connections, was always within the clinically determined epileptogenic zone that ended up being resected at surgery (van Mierlo et al, 2014).…”

Advances of Intracranial Electroencephalography in Localizing the Epileptogenic Zone

“…Analysis of iEEG using computational models provides additional useful information on the epileptogenic network in the resting state or during the propagation of ictal discharges. One study analyzed the resting-state coherence of the EEG frequency band between 5 and 50 Hz in TLE, and found that patients who had stronger and more heterogeneous connections within the temporal lobe were more prone to seizure recurrence [83]. Other studies have focused on ictal studies.…”

Spatiotemporal Mapping of Interictal Spike Propagation: A Novel Methodology Applied to Pediatric Intracranial EEG Recordings

“…Indeed, in recent years, network analysis of EEG recordings has emerged as a major area of research (40, 41). Researchers have used principles from network science and graph theory to localize the EZ (42, 43), examine the events surrounding ictal onset (44) and predict surgical outcome (45) with increasing levels of success. Spike propagation is an intuitive method for visualizing connectivity patterns within the EZ, allowing researchers to quantify both the strength and directionality of pairwise connections (i.e., how often is a spike transmitted from channel A to B , and vice versa).…”