Effect of Introducing time component on the EEG inverse problem

The electroencephalography is a widely used technique with a better temporal resolution, which measures the potential difference between various locations on the scalp. The EEG inverse problem for localization of neural electrical current is an ill-posed problem, that is to say, an infinite number of current distribution in the head volume can produce the same potential distribution on the surface. To this end, many resolution methods exist. This paper presents a spatio-temporal resolution of the Inverse Problem (IP). In fact, the study of the temporal component is important to improve the localization performances. Since, we will focus on the conventional method: Minimum norm solution MN, weighted minimum norm solution WMN and standardized Low resolution brain electromagnetic tomography sLORETA. The main objective of this study is to highlight the effect of the temporal component on the brain activity localization. We demonstrated that the integration of the time component could reduce the localization error value.