  In recent years, multiple noninvasive imaging modalities have been used to
develop a better understanding of the human brain functionality, including
positron emission tomography, single-photon emission computed tomography, and
functional magnetic resonance imaging, all of which provide brain images with
millimeter spatial resolutions. Despite good spatial resolution, time
resolution of these methods are poor and values are about seconds.
Electroencephalography (EEG) is a popular non-invasive electrophysiological
technique of relatively very high time resolution which is used to measure
electric potential of brain neural activity. Scalp EEG recordings can be used
to perform the inverse problem in order to specify the location of the dominant
sources of the brain activity. In this paper, EEG source localization research
is clustered as follows: solving the inverse problem by statistical method
(37.5%), diagnosis of brain abnormalities using common EEG source localization
methods (18.33%), improving EEG source localization methods by non-statistical
strategies (3.33%), investigating the effect of the head model on EEG source
imaging results (12.5%), detection of epileptic seizures by brain activity
localization based on EEG signals (20%), diagnosis and treatment of ADHD
abnormalities (8.33%). Among the available methods, minimum norm solution has
shown to be very promising for sources with different depths. This review
investigates diseases that are diagnosed using EEG source localization
techniques. In this review we provide enough evidence that the effects of
psychiatric drugs on the activity of brain sources have not been enough
investigated, which provides motivation for consideration in the future
research using EEG source localization methods.
