A review on epileptic foci localization using resting-state functional magnetic resonance imaging

Abstract

Epilepsy is a brain syndrome caused by synchronous abnormal discharge of brain neurons. As an effective treatment for epilepsy, successful surgical resection requires accurate localization of epileptic foci to avoid iatrogenic disability. Previous studies have demonstrated the potential of restingstate functional magnetic resonance imaging (rs-fMRI) technique to localize epileptic foci though clinical applications of rs-fMRI are still at an early stage of development. fMRI data analysis approaches seek pre-defined regressors modeling contributions to the voxel time series, including the BOLD response following neuronal activation. In present study, localization strategies of epileptic foci in rs-fMRI technology were classified and summarized. To begin with, data-driven approaches attempting to determine the intrinsic structure of the data were discussed in detail. Then, as novel fMRI data analysis methods, deconvolution algorithms such as total activation (TA) and blind deconvolution were discussed, which were applied to explore the underlying activity-inducing signal of the BOLD signal. Lastly, effective connectivity approaches such as autocorrelation function method and Pearson correlation coefficient have also been proposed to identify the brain regions driving the generation of seizures within the epileptic network. In the future, fMRI technology can be used as a supplement of intraoperative subdural electrode method or combined with traditional epileptic focus localization technologies, which is one of the most attractive aspect in clinic. It may also play an important role in providing diagnostic information for epilepsy patients.

Keywords

• epilepsy
• fmri
• localization of foci
• data-driven approach
• brain functional network connectivity