paperKB
coga / coga-kb
Help
Sign in

Chunk #360 — 4 Performance analysis — 4.2 Monte Carlo performance analysis of non-parametric inverse solutions — 4.2.4 Discussion of results

Source
Review on solving the inverse problem in EEG source analysis.
Embedded
yes

Text

In summary, it can be stated that for single source localization, regularized sLORETA does indeed produce solutions with the lower localization errors and least number of ghost sources; regularization has a marked effect on these results. These statistical results also showed that regularized LORETA is the second best performing algorithm in terms of both performance measures with the exception of surface sources at low noise levels. Therefore, for single source localization, the computational cost of SLF does not yield any additional benefits over the direct methods of sLORETA and LORETA. It should also be recalled that in addition to source localization, LORETA provides source orientation estimates, which are unavailable in sLORETA solutions.