# issue with inverse operator (repost) **URL:** \ **Category:** Mailing List Archive (read-only)\ **Tags:** list-archive\ **Created:** [June 3, 2011, 4:39pm UTC](https://mne.discourse.group/t/issue-with-inverse-operator-repost/314 "2011-06-03T16:39:51Z")\ **Posts on this page:** 7\ **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:** [June 3, 2011, 4:39pm UTC](https://mne.discourse.group/t/issue-with-inverse-operator-repost/314/1 "2011-06-03T16:39:51Z")
Hi all, It's been a few weeks, and I am still having trouble with this. There seems to be an issue with the inverse operator from the nightly build version of MNE. The activation shown on the brain looks unusal. I am using the nightly build because in the previous versions working with SSP for EEG affected the MEG channels and it was fixed in the nightly build. Now, I seem to be running into some trouble when using an inverse operator created from both MEG and EEG data, the MEG based inverse operator works/looks fine. Anyone have any work-arounds or solutions? Thank you -Ricky ---
**Author:** ![system](https://global.discourse-cdn.com/free1/uploads/mne/original/1X/85cc6bd2b69cb698a166dc6d880fb550510d0144.jpeg) [@system](https://mne.discourse.group/u/system)\ **Post date:** [June 3, 2011, 4:51pm UTC](https://mne.discourse.group/t/issue-with-inverse-operator-repost/314/2 "2011-06-03T16:51:15Z")
I had a problem with the EEG projection vectors affecting MEG channels as well. However, it only happened on my linux x86\_64 install, not on a linux i686 install or osx installs. As you note, this channel corruption on x86\_64 was fixed in a recent nightly. I assume, then, that you're running the linux x86\_64 nightly? If so, one thing you could try is generating your inverses using all four combinations of 1) the last stable release and 2) the latest nightly combined with 1) the x86\_64 linux version and 2) the i686 linux version. (The i686 linux version should run just fine on 64-bit linux installs.) If you can identify which of the four combinations suffers from this problem, then it could help narrow down the cause of the problem. Eric ---
**Author:** ![system](https://global.discourse-cdn.com/free1/uploads/mne/original/1X/85cc6bd2b69cb698a166dc6d880fb550510d0144.jpeg) [@system](https://mne.discourse.group/u/system)\ **Post date:** [June 6, 2011, 7:52pm UTC](https://mne.discourse.group/t/issue-with-inverse-operator-repost/314/3 "2011-06-06T19:52:27Z")
Hello Eric, We tried the stable release and the nightly build. The stable release inverse operator seems to work fine but than the issue with the projection vectors exists. With the nightly build, it's the opposite, the inverse operator gives me the issue and there seems to be no problem with the EEG and MEG projection vectors. ---
**Author:** ![system](https://global.discourse-cdn.com/free1/uploads/mne/original/1X/85cc6bd2b69cb698a166dc6d880fb550510d0144.jpeg) [@system](https://mne.discourse.group/u/system)\ **Post date:** [June 6, 2011, 7:57pm UTC](https://mne.discourse.group/t/issue-with-inverse-operator-repost/314/4 "2011-06-06T19:57:38Z")
Assuming you are running linux (are you?), were you able to test it on both x86\_64 and i686 versions? Eric ---
**Author:** ![system](https://global.discourse-cdn.com/free1/uploads/mne/original/1X/85cc6bd2b69cb698a166dc6d880fb550510d0144.jpeg) [@system](https://mne.discourse.group/u/system)\ **Post date:** [June 6, 2011, 8:24pm UTC](https://mne.discourse.group/t/issue-with-inverse-operator-repost/314/5 "2011-06-06T20:24:36Z")
Hi Ricky,    One possibly useful test to see if the issue is related to machine precision/round-off related bugs is to apply the inverse operator in MATLAB at double precision using mne\_ex\_compute\_inverse(). If that works fine, then it probably confirms a bug with mne\_make\_movie. If that also looks weird, then it could potentially point to something more upstream such as the SSP (that's used on the data) not being applied to the lead field/noise covariance correctly etc.. Regards, Hari ---
**Author:** ![system](https://global.discourse-cdn.com/free1/uploads/mne/original/1X/85cc6bd2b69cb698a166dc6d880fb550510d0144.jpeg) [@system](https://mne.discourse.group/u/system)\ **Post date:** [June 7, 2011, 8:40am UTC](https://mne.discourse.group/t/issue-with-inverse-operator-repost/314/6 "2011-06-07T08:40:47Z")
Hi Ricky, Are the MEG data maxfiltered? Sometimes the inverse operator calculation with MEG + EEG does not work correctly if maxfilter is involved. Can you send the screen output of the inverse operator calculation? - Matti ---
**Author:** ![system](https://global.discourse-cdn.com/free1/uploads/mne/original/1X/85cc6bd2b69cb698a166dc6d880fb550510d0144.jpeg) [@system](https://mne.discourse.group/u/system)\ **Post date:** [June 7, 2011, 2:47pm UTC](https://mne.discourse.group/t/issue-with-inverse-operator-repost/314/7 "2011-06-07T14:47:25Z")
Hi Matti, The output is down below. Thank you, -Ricky mne\_do\_inverse\_operator --fwd averages\_covariances/CPLEX2\_09\_merged\_avg-7-fwd.fif --senscov averages\_covariances/CPLEX2\_09\_merged\_cov.fif --eeg --meg --subject CPLEX2\_09 mne\_inverse\_operator version 2.32 compiled at Jun 7 2011 04:07:51 Compute the MNE inverse operator decomposition Forward solution : averages\_covariances/CPLEX2\_09\_merged\_avg-7-fwd.fif Noise covariance matrix : averages\_covariances/CPLEX2\_09\_merged\_cov.fif Source covariance matrix : identity matrix Destination for the inverse operator data : averages\_covariances/CPLEX2\_09\_merged\_avg-7-meg-eeg-inv.fif Include MEG and EEG data. 1 bad channels from averages\_covariances/CPLEX2\_09\_merged\_cov.fif:         \ Reading the forward solution....         Read data for 306 MEG channels and 5906 sources         Read data for 70 EEG channels and 5906 sources         Free source orientations.         The forward computation was performed in head coordinates.         1 bad channels read from the forward solution file.         305 MEG channels remained after excluding bad ones         No bad channels removed from EEG         Read 2 source spaces with a total of 5906 source locations         Source spaces are now in head coordinates.         Channel description list matched with the composite forward solution matrix.         Global Cartesian head coordinate system forward matrix will be employed. Loaded projection from averages\_covariances/CPLEX2\_09\_merged\_cov.fif:         # 1 : planar-77--0.200-0.200-PCA-01 : 1 vecs : 204 chs MEG active         # 2 : planar-77--0.200-0.200-PCA-02 : 1 vecs : 204 chs MEG active         # 3 : planar-77--0.200-0.200-PCA-03 : 1 vecs : 204 chs MEG active         # 4 : axial-77--0.200-0.200-PCA-01 : 1 vecs : 101 chs MEG active         # 5 : axial-77--0.200-0.200-PCA-02 : 1 vecs : 101 chs MEG active         # 6 : axial-77--0.200-0.200-PCA-03 : 1 vecs : 101 chs MEG active         # 7 : eeg-77--0.200-0.200-PCA-01 : 1 vecs : 70 chs EEG active         # 8 : eeg-77--0.200-0.200-PCA-02 : 1 vecs : 70 chs EEG active         # 9 : eeg-77--0.200-0.200-PCA-03 : 1 vecs : 70 chs EEG active         # 10 : axial-PCA-01 : 1 vecs : 102 chs MEG active         # 11 : axial-PCA-02 : 1 vecs : 102 chs MEG active         # 12 : axial-PCA-03 : 1 vecs : 102 chs MEG active         # 13 : axial-PCA-04 : 1 vecs : 102 chs MEG active         # 14 : Average EEG reference : 1 vecs : 70 chs EEG active Read a full noise covariance matrix from averages\_covariances/CPLEX2\_09\_merged\_cov.fif Picked appropriate channels from the sensor noise covariance matrix. MEG/EEG correlations omitted. No regularization applied to the noise-covariance matrix Projection applied to the covariance matrix. Decomposing the noise covariance...         Estimated covariance matrix rank = 361 (0.000178757)         293 MEG and 68 EEG-like channels in the whitened data done. Creating the source covariance matrix: 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 = 0.987327         scaling factor to adjust the trace = 19 (nchan = 375 nzero = 14) done Writing the solution to averages\_covariances/CPLEX2\_09\_merged\_avg-7-meg-eeg-inv.fif...done Attaching the environment to averages\_covariances/CPLEX2\_09\_merged\_avg-7-meg-eeg-inv.fif...done Inverse operator file averages\_covariances/CPLEX2\_09\_merged\_avg-7-meg-eeg-inv.fif ready. Thank you for waiting.