document: Model selection in electromagnetic source analysis with an application to VEFs In electromagnetic source analysis , it is necessary to determine how many sources are required to describe the electroencephalogram or magnetoencephalogram adequately . Model selection procedures -LRB- MSPs -RRB- or goodness of fit procedures give an estimate of the required number of sources . Existing and new MSPs are evaluated in different source and noise settings : two sources which are close or distant and noise which is uncorrelated or correlated . The commonly used MSP residual variance is seen to be ineffective , that is it often selects too many sources . Alternatives like the adjusted Hotelling 's test , Bayes information criterion and the Wald test on source amplitudes are seen to be effective . The adjusted Hotelling 's test is recommended if a conservative approach is taken and MSPs such as Bayes information criterion or the Wald test on source amplitudes are recommended if a more liberal approach is desirable . The MSPs are applied to empirical data -LRB- visual evoked fields -RRB-
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