Research

Effects of dipole position, orientation and noise on the accuracy of EEG source localization

Kevin Whittingstall¹ , Gerhard Stroink¹ , Larry Gates² , JF Connolly³ and Allen Finley⁴

¹Department of Physics, Dalhousie University, Halifax NS, Canada

²Department of Radiation Oncology, QEII Health Centre, Halifax, Canada

³Department of Psychology, Dalhousie University, Canada

⁴Department of Anaesthesia, Dalhousie University, Halifax, Canada

author email corresponding author email

BioMedical Engineering OnLine 2003, 2:14doi:10.1186/1475-925X-2-14

Published:	6 June 2003

Abstract

Background

The electroencephalogram (EEG) reflects the electrical activity in the brain on the surface of scalp. A major challenge in this field is the localization of sources in the brain responsible for eliciting the EEG signal measured at the scalp. In order to estimate the location of these sources, one must correctly model the sources, i.e., dipoles, as well as the volume conductor in which the resulting currents flow. In this study, we investigate the effects of dipole depth and orientation on source localization with varying sets of simulated random noise in 4 realistic head models.

Methods

Dipole simulations were performed using realistic head models and using the boundary element method (BEM). In all, 92 dipole locations placed in temporal and parietal regions of the head with varying depth and orientation were investigated along with 6 different levels of simulated random noise. Localization errors due to dipole depth, orientation and noise were investigated.

Results

The results indicate that there are no significant differences in localization error due tangential and radial dipoles. With high levels of simulated Gaussian noise, localization errors are depth-dependant. For low levels of added noise, errors are similar for both deep and superficial sources.

Conclusion

It was found that if the signal-to-noise ratio is above a certain threshold, localization errors in realistic head models are, on average the same for deep and superficial sources. As the noise increases, localization errors increase, particularly for deep sources.