Summary: Purpose: Fifteen percent to 25% of patients with refractory epilepsy require invasive video–electroencephalography (EEG) monitoring (IVEM) to precisely delineate the ictal‐onset zone. This delineation based on the recorded intracranial EEG (iEEG) signals occurs visually by the epileptologist and is therefore prone to human mistakes. The purpose of this study is to investigate whether effective connectivity analysis of intracranially recorded EEG during seizures provides an objective method to localize the ictal‐onset zone.Methods: In this study data were analyzed from eight patients who underwent IVEM at Ghent University Hospital in Belgium. All patients had a focal ictal onset and were seizure‐free following resective surgery. The effective connectivity pattern was calculated during the first 20 s of ictal rhythmic iEEG activity. The out‐degree, which is reflective of the number of outgoing connections, was calculated for each electrode contact for every single seizure during these 20 s. The seizure specific out‐degrees were summed per patient to obtain the total out‐degree. The electrode contact with the highest total out‐degree was considered indicative of localization of the ictal‐onset zone. This result was compared to the conclusion of the visual analysis of the epileptologist and the resected brain region segmented from postoperative magnetic resonance imaging (MRI).Key findings: In all eight patients the electrode contact with the highest total out‐degree was among the contacts identified by the epileptologist as the ictal onset. This contact, that we named “the driver,” always laid within the resected brain region. Furthermore, the patient‐specific connectivity patterns were consistent over the majority of seizures.Significance: In this study we demonstrated the feasibility of correctly localizing the ictal‐onset zone from iEEG recordings by using effective connectivity analysis during the first 20 s of ictal rhythmic iEEG activity.

Electroencephalographic (EEG) source imaging localizes the generators of neural activity in the brain. During presurgical epilepsy evaluation, EEG source imaging of interictal epileptiform discharges is an established tool to estimate the irritative zone. However, the origin of interictal activity can be partly or fully discordant with the origin of seizures. Therefore, source imaging based on ictal EEG data to determine the seizure onset zone can provide precious clinical information. In this descriptive review, we address the importance of localizing the seizure onset zone based on noninvasive EEG recordings as a complementary analysis that might reduce the burden of the presurgical evaluation. We identify three major challenges (low signal-to-noise ratio of the ictal EEG data, spread of ictal activity in the brain, and validation of the developed methods) and discuss practical solutions. We provide an extensive overview of the existing clinical studies to illustrate the potential clinical utility of EEG-based localization of the seizure onset zone. Finally, we conclude with future perspectives and the needs for translating ictal EEG source imaging into clinical practice.

Objective: The importance of functional brain connectivity to study physiological and pathological brain activity has been widely recognized. Here, we aimed to 1) review a methodological pipeline to investigate directed functional connectivity between brain regions using source signals derived from high-density EEG; 2) elaborate on some methodological challenges; and 3) apply this pipeline to temporal lobe epilepsy (TLE) patients and healthy controls to investigate directed functional connectivity differences in the theta and beta frequency bands during EEG epochs without visible pathological activity. Methods: The methodological pipeline includes: EEG acquisition and preprocessing, electrical-source imaging (ESI) using individual head models and distributed inverse solutions, parcellation of the gray matter in regions of interest, fixation of the dipole orientation for each region, computation of the spectral power in the source space, and directed functional connectivity estimation using Granger-causal modeling. We specifically analyzed how the signal-to-noise ratio (SNR) changes using different approaches for the dipole orientation fixation. We applied this pipeline to 20 left TLE patients, 20 right TLE patients, and 20 healthy controls. Results: Projecting each dipole to the predominant dipole orientation leads to a threefold SNR increase as compared to the norm of the dipoles. By comparing connectivity in TLE versus controls, we found significant frequency-specific outflow differences in physiologically plausible regions. Conclusion: The results suggest that directed functional connectivity derived from ESI can help better understand frequency-specific resting-state network alterations underlying focal epilepsy. Significance: EEG-based directed functional connectivity could contribute to the search of new biomarkers of this disorder.