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
网易YEAH.NET免费邮箱：您的终身免费邮箱
