Another technique similar to SSLOFO in that it can capture spatial and temporal information is the ST-MAP [4]. If only spatial information is taken into account, the so called S-MAP succeeds in recovering most edges, preserving the global temporal shape but with possible sharp magnitude variations. The ST-MAP however gives a much smoother reconstruction of dipoles which helps stabilize the algorithm and reduce the computation time by 22% when compared to the S-MAP. These results were compared to those obtained by Quadratic Regularization (QR) and LORETA and the error measures were based on the data fit and reconstruction error. S-MAP and ST-MAP were both found to be superior to these algorithms as they give much smoother solutions and reasonably lower reconstruction errors [4].
