A framework to integrate EEG-correlated fMRI and intracerebral recordings

Abstract

EEG-correlated functional MRI (EEG-fMRI) has been used to indicate brain regions associated with interictal epileptiform discharges (IEDs). This technique enables the delineation of the complete epileptiform network, including multifocal and deeply situated cortical areas. Before EEG-fMRI can be used as an additional diagnostic tool in the preoperative work-up, its added value should be assessed in relation to intracranial EEG recorded from depth electrodes (SEEG) or from the cortex (ECoG), currently the clinical standard. In this study, we propose a framework for the analysis of the SEEG data to investigate in a quantitative way whether EEG-fMRI reflects the same cortical areas as identified by the IEDs present in SEEG recordings. For that purpose, the data of both modalities were analyzed with a general linear model at the same time scale and within the same spatial domain. The IEDs were used as predictors in the model, yielding for EEG-fMRI the brain voxels that were related to the IEDs and, similarly for SEEG, the electrodes that were involved. Finally, the results of the regression analysis were projected on the anatomical MRI of the patients. To explore the usefulness of this quantitative approach, a sample of five patients was studied who both underwent EEG-fMRI and SEEG recordings. For clinical validation, the results of the SEEG analysis were compared to the standard visual review of IEDs in SEEG and to the identified seizure onset zone, the resected area, and outcome of surgery. SEEG analysis revealed a spatial pattern for the most frequent and dominant IEDs present in the data of all patients. The electrodes with the highest correlation values were in good concordance with the electrodes that showed maximal amplitude during those events in the SEEG recordings. These results indicate that the analysis of SEEG data at the time scale of EEG-fMRI, using the same type of regression model, is a promising way to validate EEG-fMRI data. In fact, the BOLD areas with a positive hemodynamic response function were closely related to the spatial pattern of IEDs in the SEEG recordings in four of the five patients. The areas of significant BOLD that were not located in the vicinity of depth electrodes, were mainly characterized by negative hemodynamic responses. Furthermore, the area with a positive hemodynamic response function overlapped with the resected area in three patients, while it was located at the edge of the resection area for one. To conclude, the results of this study encourage the application of EEG-fMRI to guide the implantation of depth electrodes as prerequisite for successful epilepsy surgery.