I’m following nilearn’s tutorial with the AHDH dataset.

```
design_matrix = make_first_level_design_matrix(frametimes, hrf_model='spm',
add_regs=seed_time_series,
add_reg_names=["pcc_seed"])
first_level_model = FirstLevelModel(t_r=t_r, slice_time_ref=slice_time_ref)
first_level_model = first_level_model.fit(run_imgs=adhd_dataset.func[0],
design_matrices=design_matrix)
```

I have a few questions:

- all options common in
`make_first_level_design_matrix`

and`FirstLevelModel`

have to be exactly the same right? For example, if I define`drift_model='cosine'`

in`make_first_level_design_matrix`

do I need to do the same in`FirstLevelModel`

? Or does`FirstLevelModel`

ignores its options if`design_matrices`

are given? - Since the AHDH dataset are resting state data, why do I need an
`hrf_model`

? - Is there an option to inform
`FirstLevelModel`

that I haven’t performed slice timing correction? -
`make_first_level_design_matrix`

adds a constant to the design matrix automatically. However my data have been already demeaned, is this column still required? - Also what should the
`output_type`

be if I intend to use these images in a group level analysis?