Hi,
I used uber_subject.py to do my (single subject) analysis and got a bunch of files. I understand at least some of them, but I was wondering if there is a way to access the registered/aligned EPI volumes.
Here are all the files I got:
3dClustSim.cmd* mat.r01.vr.aff12.1D*
all_runs.Imag_anat2epi.nii.gz* mat.r01.warp.aff12.1D*
all_runs.Imag_anat2epi+tlrc.BRIK* motion_demean.1D*
all_runs.Imag_anat2epi+tlrc.HEAD* motion_deriv.1D*
anat_final.Imag_anat2epi.nii.gz* motion_Imag_anat2epi_censor.1D*
anat_final.Imag_anat2epi+tlrc.BRIK* motion_Imag_anat2epi_CENSORTR.txt*
anat_final.Imag_anat2epi+tlrc.HEAD* motion_Imag_anat2epi_enorm.1D*
blur.epits.1D* MPRAGEco_al_junk_mat.aff12.1D*
blur.err_reml.1D* MPRAGEco_al_junk+orig.BRIK*
blur.errts.1D* MPRAGEco_al_junk+orig.HEAD*
blur_est.Imag_anat2epi.1D* MPRAGEco_ns+orig.BRIK*
brick2p.nii.gz* MPRAGEco_ns+orig.HEAD*
brick2t.nii.gz* MPRAGEco_ns+tlrc.BRIK*
ClustSim.mask* MPRAGEco_ns+tlrc.HEAD*
ClustSim.NN1_1sided.1D* MPRAGEco_ns_WarpDrive.log*
ClustSim.NN1_1sided.niml* MPRAGEco_ns.Xaff12.1D*
ClustSim.NN1_2sided.1D* MPRAGEco_ns.Xat.1D*
ClustSim.NN1_2sided.niml* MPRAGEco+orig.BRIK*
ClustSim.NN1_bisided.1D* MPRAGEco+orig.HEAD*
ClustSim.NN1_bisided.niml* out.cormat_warn.txt*
ClustSim.NN2_1sided.1D* outcount.r01.1D*
ClustSim.NN2_1sided.niml* outcount_rall.1D*
ClustSim.NN2_2sided.1D* out.gcor.1D*
ClustSim.NN2_2sided.niml* out.mask_ae_corr.txt*
ClustSim.NN2_bisided.1D* out.mask_ae_overlap.txt*
ClustSim.NN2_bisided.niml* out.pre_ss_warn.txt*
ClustSim.NN3_1sided.1D* out.ss_review.Imag_anat2epi.txt*
ClustSim.NN3_1sided.niml* pb00.Imag_anat2epi.r01.tcat+orig.BRIK*
ClustSim.NN3_2sided.1D* pb00.Imag_anat2epi.r01.tcat+orig.HEAD*
ClustSim.NN3_2sided.niml* pb01.Imag_anat2epi.r01.tshift+orig.BRIK*
ClustSim.NN3_bisided.1D* pb01.Imag_anat2epi.r01.tshift+orig.HEAD*
ClustSim.NN3_bisided.niml* pb02.Imag_anat2epi.r01.volreg+tlrc.BRIK*
corr_brain+tlrc.BRIK* pb02.Imag_anat2epi.r01.volreg+tlrc.HEAD*
corr_brain+tlrc.HEAD* pb03.Imag_anat2epi.r01.blur+tlrc.BRIK*
dfile.r01.1D* pb03.Imag_anat2epi.r01.blur+tlrc.HEAD*
dfile_rall.1D* pb04.Imag_anat2epi.r01.scale+tlrc.BRIK*
@epi_review.Imag_anat2epi* pb04.Imag_anat2epi.r01.scale+tlrc.HEAD*
errts.Imag_anat2epi_REML+tlrc.BRIK* @ss_review_basic*
errts.Imag_anat2epi_REML+tlrc.HEAD* @ss_review_driver*
errts.Imag_anat2epi+tlrc.BRIK* @ss_review_driver_commands*
errts.Imag_anat2epi+tlrc.HEAD* stats.Imag_anat2epi_REML+tlrc.BRIK*
fitts.Imag_anat2epi_REML+tlrc.BRIK* stats.Imag_anat2epi_REML+tlrc.HEAD*
fitts.Imag_anat2epi_REML+tlrc.HEAD* stats.Imag_anat2epi_REMLvar+tlrc.BRIK*
fitts.Imag_anat2epi+tlrc.BRIK* stats.Imag_anat2epi_REMLvar+tlrc.HEAD*
fitts.Imag_anat2epi+tlrc.HEAD* stats.Imag_anat2epi+tlrc.BRIK*
full_mask.Imag_anat2epi+tlrc.BRIK* stats.Imag_anat2epi+tlrc.HEAD*
full_mask.Imag_anat2epi+tlrc.HEAD* stats.REML_cmd*
gmean.errts.unit.1D* stimuli/
ideal_stim_times.1D.1D* suma_mni/
Imagination-segmentation-K2.nii.gz* sum_ideal.1D*
Imagination-segmentation.nii.gz* TSNR.Imag_anat2epi+tlrc.BRIK*
mask_anat.Imag_anat2epi+tlrc.BRIK* TSNR.Imag_anat2epi+tlrc.HEAD*
mask_anat.Imag_anat2epi+tlrc.HEAD* X.jpg*
mask_epi_extents+tlrc.BRIK* X.nocensor.xmat.1D*
mask_epi_extents+tlrc.HEAD* X.stim.xmat.1D*
mask_group+tlrc.BRIK* X.xmat.1D*
mask_group+tlrc.HEAD*
Many thanks and best wishes,
Ranjan
