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To construct the L2 MNE operator, we used the following formula found in the lecture slides:  $$P_{MNE}=RL^T(LRL^T + \lambda C_n)^{-1}$$  The following Matlab script was used in the simple case without depth weighting.  \begin{verbatim}  load ex3_data.mat  L2=L*L';  snr = sqrt(n_trial);  lambda = trace(L2)/(trace(Cn)*snr^2)  p_mne=L'*pinv(L2+lambda*Cn,1e-24);  src1 = p_mne*data1;  src2 = p_mne*data2;  \end{verbatim}  Here an identity matrix was used for the source covariance matrix. Next, to include depth weighting, we modified the source covariance matrix:  \begin{verbatim}  W_i = diag(sqrt(sum(L,1).^2./306));  lambda = trace(L*W_i*L')/(trace(Cn)*snr^2)  pw_mne=W_i*L'*pinv(L*W_i*L'+lambda*Cn,1e-20);  srcw1 = pw_mne*data1;   srcw2 = pw_mne*data2;  \end{verbatim}