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Dear Haiteng, Those warnings are normal and are not the reason why your results do not make sense. I think if you choose 'Single sphere' model there will be no warnings but the results should not be very different. Imaging source reconstruction even with very sophisticated methods used in SPM is not guaranteed to give you the right answer. You can try to improve the results by limiting the time window to the part you are interested in and/or filtering your data in a narrower band around the frequencies you expect to contain your physiological signals. Try playing with different options in the 'Custom' button. If you don't manage to make any progress, send us an example of your data and some details about the paradigm and we'll look at at it. How long is your ERP? Is it 2 min? If so I wouldn't be surprised 3D may fail. Best, Vladimir 2009/7/27 hiten <[log in to unmask]>: > Dear SPMers: > After pre-processing ,I load MEEG dataset which is averaged to do 3D source > reconstruction .I use the subject's sMRI,choose 'normal' mesh,select our > used nasion and preauricular points as fiducials,then go to the Forward > computation using single shell model ,following warning arises: > using headmodel specified in the configuration > using gradiometers specified in the configuration > computing surface normals > Warning: Matrix is close to singular or badly scaled. > Results may be inaccurate. RCOND = 4.227452e-017. >> In fieldtrip\private\meg_ini>getcoeffs at 94 > In fieldtrip\private\meg_ini at 36 > In fieldtrip\private\prepare_vol_sens at 270 > In fieldtrip\private\prepare_headmodel at 223 > In fieldtrip\private\headmodelplot at 205 > In ft_headmodelplot at 11 > In spm_eeg_inv_checkforward at 70 > In spm_eeg_inv_forward_ui at 48 > In spm_eeg_inv_imag_api>Forward_Callback at 87 > In spm_eeg_inv_imag_api at 53 > undoing the G3BR balancing > undoing the G3BR balancing > Foward model complete - thank you > Ignoring that ,next I choose "Standard" inversion,produciing below > warnings: > computing surface normals > Warning: Matrix is close to singular or badly scaled. > Results may be inaccurate. RCOND = 4.206769e-017. >> In forwinv\private\meg_ini>getcoeffs at 94 > In forwinv\private\meg_ini at 36 > In forwinv\private\prepare_vol_sens at 270 > In forwinv_prepare_vol_sens at 11 > In spm_eeg_lgainmat at 91 > In spm_eeg_invert at 115 > In spm_eeg_invert_ui at 95 > In spm_eeg_inv_imag_api>Inverse_Callback at 94 > In spm_eeg_inv_imag_api at 53 > NB :According to my test paradigm, the inverse result can not make sense at > all. > Any suggestion? Thanks in advance! > > > -- > haiteng jiang > Research Center for Learning Science, > Southeast University > Si Pai Lou 2 # , Nanjing, 210096, P.R.China > Brain Imaging Lab > Email: jianghaiteng@126com > > > ________________________________ > 网易YEAH.NET免费邮箱：您的终身免费邮箱