# mne\_do\_inverse\_operator **URL:** \ **Category:** Mailing List Archive (read-only)\ **Tags:** list-archive\ **Created:** [May 1, 2014, 3:37pm UTC](https://mne.discourse.group/t/mne-do-inverse-operator/720 "2014-05-01T15:37:35Z")\ **Posts on this page:** 2\ **Page:** 1
**Author:** ![system](https://global.discourse-cdn.com/free1/uploads/mne/original/1X/85cc6bd2b69cb698a166dc6d880fb550510d0144.jpeg) [@system](https://mne.discourse.group/u/system)\ **Post date:** [May 1, 2014, 3:37pm UTC](https://mne.discourse.group/t/mne-do-inverse-operator/720/1 "2014-05-01T15:37:35Z")
Dear MNE Experts, I suspect this is a question for Matti, but of course I'll be happy to get help from anyone. When I launch mne\_do\_inverse\_operator, it goes through the whole process, then at the very end it gives a "Segmentation fault". Oddly, I have a group of 20 participants, all analyzed the same way, but it only does this for one of them. I'd appreciate any help/insight you can give. Here's the full screen output, in case it helps: wgraves at argus:~/data/ld\_fmri/data/4803/freesurf/4803/MEG/run03\_lexdec01\> mne\_do\_inverse\_operator --fwd $megdir/$rundir/${meas}-ico-4-fwd.fif --fixed --depth --megreg 0.1 --noisecov $megdir/$rundir/$cov mne\_inverse\_operator version 2.33 compiled at Aug 14 2013 04:19:05 Compute the MNE inverse operator decomposition Forward solution : /home/wgraves/data/ld\_fmri/data/4803/freesurf/4803/MEG/run03\_lexdec01/run03\_xtraClean\_0.1\_40Hz\_word\_nonword\_ave-ico-4-fwd.fif Noise covariance matrix : /home/wgraves/data/ld\_fmri/data/4803/freesurf/4803/MEG/run03\_lexdec01/run03\_xtraClean\_0.1\_40Hz\_word\_nonword-cov.fif Source covariance matrix : identity matrix Destination for the inverse operator data : /home/wgraves/data/ld\_fmri/data/4803/freesurf/4803/MEG/run03\_lexdec01/run03\_xtraClean\_0.1\_40Hz\_word\_nonword\_ave-ico-4-meg-fixed-inv.fif Include MEG data. Noise-covariance regularization (mag) : 0.10 Noise-covariance regularization (grad) : 0.10 Employ depth weighting.         limit = 10.00         exponent = 0.80 Reading the forward solution....         Read data for 306 MEG channels and 5112 sources         Free source orientations.         The forward computation was performed in head coordinates.         Read 2 source spaces with a total of 5112 source locations         Source spaces are now in head coordinates.         Channel description list matched with the composite forward solution matrix.         Local surface coordinate system forward matrix will be employed. Loaded projection from /home/wgraves/data/ld\_fmri/data/4803/freesurf/4803/MEG/run03\_lexdec01/run03\_xtraClean\_0.1\_40Hz\_word\_nonword-cov.fif:         # 1 : planar-999--0.080-0.080-PCA-01 : 1 vecs : 204 chs MEG active         # 2 : axial-999--0.080-0.080-PCA-01 : 1 vecs : 102 chs MEG active         # 3 : planar-801--0.200-0.200-PCA-01 : 1 vecs : 204 chs MEG active         # 4 : axial-801--0.200-0.200-PCA-01 : 1 vecs : 102 chs MEG active Read a full noise covariance matrix from /home/wgraves/data/ld\_fmri/data/4803/freesurf/4803/MEG/run03\_lexdec01/run03\_xtraClean\_0.1\_40Hz\_word\_nonword-cov.fif Picked appropriate channels from the sensor noise covariance matrix. MEG/EEG correlations omitted. Average noise-covariance matrix diagonals:         Magnetometers : 170.14 fT reg = 0.10         Planar gradiometers : 38.99 fT/cm reg = 0.10 Noise-covariance regularized as requested. Projection applied to the covariance matrix. Decomposing the noise covariance...         Estimated covariance matrix rank = 302 (0.00206112)         302 MEG and 0 EEG-like channels remain in the whitened data done. Creating the depth weighting matrix...         204 planar channels         limit = 3613/5112 = 10.000623         scale = 2.06846e-07 exp = 0.8         Picked elements from a free-orientation depth-weighting prior into the fixed-orientation one.         Converted the forward solution into the fixed-orientation mode. Creating the source covariance matrix:         Depth-weighting applied. done Applying linear projection to the forward solution...done Whitening the forward solution...done Scaling the source covariance...done Decomposing...         Applying a priori source weighting to the forward solution...done         Transpose...done         SVD...done         largest singular value = 0.171679         scaling factor to adjust the trace = 25.2724 (nchan = 306 nzero = 4) done Writing the solution to /home/wgraves/data/ld\_fmri/data/4803/freesurf/4803/MEG/run03\_lexdec01/run03\_xtraClean\_0.1\_40Hz\_word\_nonword\_ave-ico-4-meg-fixed-inv.fif...Segmentation fault Inverse operator decomposition failed (see above) Thanks in advance, Will ---
**Author:** ![system](https://global.discourse-cdn.com/free1/uploads/mne/original/1X/85cc6bd2b69cb698a166dc6d880fb550510d0144.jpeg) [@system](https://mne.discourse.group/u/system)\ **Post date:** [May 1, 2014, 3:51pm UTC](https://mne.discourse.group/t/mne-do-inverse-operator/720/2 "2014-05-01T15:51:47Z")
Hi, How much free disk space is there? df -h $megdir/$rundir/ HTH D