The resolution of your functional data is likely much lower than that of the atlas. You need to resample the atlas to be the same grid of the dataset. For example here, you might use:
3dresample -master funcdset.nii -inset atlasdset.nii.gz -rmode NN -prefix atlas_rs.nii.gz
This assumes the functional dataset is in the same template "space" as the atlas by aligning to the appropriate template, in this case, MNI_2009c. Your example shows using @auto_tlrc, but that only does an affine transformation. It doesn't do a nonlinear alignment to align the data much better than that of an affine alignment alone. For that, you would probably use @SSwarper to compute the transformation of your anatomical data to the MNI 2009c template space. That program computes both affine and nonlinear alignment and skullstrips the dataset too. The EPI to anatomical alignment can be combined with that anatomical to template transformation. afni_proc.py is probably the easiest way to do all the combinations needed (motion correction, obliquity, EPI-anat, anat-template).
