Issue with 3dwarpDrive with MEICA.py

[sameera2004]

Hi,

I got the following error

++ 3dWarpDrive: AFNI version=AFNI_17.2.05 (Jul 27 2017) [64-bit] ++ Authored by: RW Cox cp: cannot stat â<80><98>S13015_T1w_MPR_BIC_v1_7_do_at.niiâ<80><99>: No such file or directory

S13015_T1w_MPR_BIC_v1_7_do_at.nii.gz file is there inside the subject directory , But still it produce the above error.

Did anyone experience this error before?Or do you know how to fix the issue?

I called meica.py with following options. meica.py -d "After_sl_S13015_Insight1_echo1.nii,After_sl_S13015_Insight1_echo2.nii,After_sl_S13015_Insight1_echo3.nii" -e 10.8,28.68,46.56 -a S13015_T1w_MPR_BIC_v1_7.nii --qwarp --MNI --no_skullstrip --fres=3.6 --prefix Insight_1 --OVERWRITE

Thank you Sameera

[sameera2004]

I missed some options earlier, Following way I called the meica.py

meica.py -d "After_sl_S13015_Insight1_echo1.nii,After_sl_S13015_Insight1_echo2.nii,After_sl_S13015_Insight1_echo3.nii" -e 10.8,28.68,46.56 -a S13015_T1w_MPR_BIC_v1_7.nii --qwarp --MNI --no_skullstrip --mask_mode=template --prefix Insight_1 --OVERWRITE

[dowdlelt]

Hi @sameera2004 MEICA is no long being maintained and we are encouraging users to move towards using tedana - with preprocessing done with other software (often afni_proc.py). See my reply in #17 for more information.

Now, that said, it looks like you said the anatomical file is *.nii.gz, but in the MEICA it is looking for just a .nii. Do you have AFNI set to always compress or some other flag? It seems that it wanted it to be uncompressed, but it was not. An alternative is just to edit the script produced by MEICA to add a gunzip command just before the line where it loads the .nii file. Then, run that directly.

Good luck

[sameera2004]

Thanks @dowdlelt for the reply. I made a mistake , S13015_T1w_MPR_BIC_v1_7_do_at.nii.gz file is not there following but this file is there S13015_T1w_MPR_BIC_v1_7_do.nii.gz.

I will take a look at Tedana with processing done with other software.

We are already looking into fMRIprep, however, I don't know how to provide all the MEICA options on fMRIprep. Have you used fMRIprep for multi echo data? Do you know where I can find a tutorial for that?

[dowdlelt]

I believe multiecho integration with fmriprep is still ongoing, but I'm not certain. I believe the best place to get help with that would be neurostars.org - in fact it looks like this was recently brought up here: https://neurostars.org/t/combining-fmriprep-with-me-ica-from-tedana/3710

If I find out more, I'll reply here.

[sameera2004]

@dowdlelt I was looking at afni_proc.py documentation, Can I use in following way to pre-processing and combine them with Tedana.

Example 12c. Multi-echo data processing - ME-ICA resting state. ~2~

     As above, but run tedana.py for MEICA denoising.

As above, but run tedana.py for MEICA denoising.

     o Since tedana.py will mask the data, it may be preferable to
       blur only within that mask (-blur_in_mask yes).
     o A task analysis using tedana might look much the same,
       but with the extra -regress options for the tasks.

            afni_proc.py -subj_id FT.12a.ME                 \
              -blocks tshift align tlrc volreg mask combine \
                      blur scale regress                    \
              -copy_anat FT_anat+orig                       \
              -dsets_me_run epi_run1_echo*.nii              \
              -echo_times 15 30.5 41                        \
              -reg_echo 2                                   \
              -tcat_remove_first_trs 2                      \
              -align_opts_aea -cost lpc+ZZ                  \
              -tlrc_base MNI152_T1_2009c+tlrc               \
              -tlrc_NL_warp                                 \
              -volreg_align_to MIN_OUTLIER                  \
              -volreg_align_e2a                             \
              -volreg_tlrc_warp                             \
              -mask_epi_anat yes                            \
              -combine_method tedana                        \
              -blur_in_mask yes                             \
              -regress_motion_per_run                       \
              -regress_censor_motion 0.2                    \
              -regress_censor_outliers 0.1                  \
              -regress_apply_mot_types demean deriv         \
              -regress_est_blur_epits

     Consider an alternative combine method, 'tedana_OC_tedort'.

[dowdlelt]

You can use those examples, however the version of tedana included with AFNI is older. It is somewhat stable, and should work - however work is continuing on tedana to get bugs squashed and make everything work better. I haven't tried to use the tedana with AFNI in quite some time. It is also possible to direct AFNI to use a user-installed tedana version. details are in afni proc.

An alternative is to run one AFNI proc - up through volreg/tlrc. This will apply all transformations equally to all echoes. You can then use tedana.py from github to combine/denoise the data (it can load BRIKs without issue), and then run a second afni_proc.py command to perform regression with the denoised data.

This is a bit harder (and may not be idea), but it does use the latest version. The development team is aware that these methods are less than optimal, and one somewhat nearterm goal is to get the latest version stable and included with afni.

Let me know if that doesn't make sense

[sameera2004]

@dowdlelt Thank you for the explanation.

Yes looks like little bit harder, but I am working on it. I already requested for tedena.py installation on our cluster.

Do you think if I use fMRIprep will it be much easier? Which one will provide better results?