# Interference Suppression in EEG Dipole Source Localization through Reduced-Rank Beamforming
## 5 Conclusions  
We proposed two neural indices for the problem of dipole source localization. These indices were designed specifically to suppress interference that are commonly present in EEG data and are often considered as \"background\" activation. Our approach comes from a combination of two different processing elements that are implemented under the structure of the GSC in order to improve the estimation and later cancellation of noise and interference, regardless of the SINR. Those elements are (i) an ABM that achieves an optimal estimation of unwanted signals and defines the rank-reduction that (ii) a CSM-based approach will apply to the filter to improve the affinity to the noise subspace. We showed the applicability of our methods for dipole source localization using real data in which LCMV-based methods could not be used given the ill-conditioned nature of the problem. We also showed that our beamformers are capable of estimating real sources from SSVEP.  
There are many factors that can affect the accuracy of the EEG source localization methods, such as the effects of the head cavities, variations in tissue conductivities, or errors in the position of the electrodes. Hence, in addition to improve the localization methods with techniques such as those we proposed here, other strategies need to be placed in practice to reduce the adverse effects previously mentioned. Even beamforming techniques such as the ones proposed here suffer a fundamental limitation: their performance directly depends on the number of sensing elements (aperture), independently of the number of time samples or the signal-to-noise ratio. Again, it is only through overlapping approaches that non-invasive localization methods of the sources in the brain can be used to diagnose pathological, physiological, mental, and functional abnormalities such as the study of localized epilepsy, evoked-related-potentials or attention deficit/hyperactivity disorder [1].  
Conceptualization, D.G.; Data curation, E.J.-C.; Formal analysis, E.J.-C.; Investigation, E.J.-C.; Methodology, E.J.-C. and D.G.; Project administration, D.G.; Resources, E.J.-C.; Software, E.J.-C. and D.G.; Supervision, D.G.; Validation, E.J.-C. and D.G.; Visualization, D.G.; Writing--original draft, E.J.-C.; Writing--review and editing, D.G. All authors have read and agreed to the published version of the manuscript.  
The work of [PERSON] was sponsored by the Mexican Council of Science and Technology (CONACyT) through the graduate school scholarship no. 727361.  
The real data used in this paper was acquired in accordance with the Declaration of Helsinki, and approved by the Ethics Committees of the Third Neurological Clinic of the Aristotle University of Thessaloniki, Muscular dystrophy Association Hellas, and Spinal Cord Injury Rehabilitation Center of Sheba Medical Center, all in Greece.  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.  
The data sets used in this study are available under request by contacting the corresponding author.  
The authors declare no conflict of interest.