code: def _make_design_matrix_slm_oasis(
      oasis_dataset, n_subjects
  ):  # pragma: no cover # noqa
      age = oasis_dataset.ext_vars["age"].astype(float)
      sex = oasis_dataset.ext_vars["mf"] == "F"
      intercept = np.ones(n_subjects)
      design_matrix = pd.DataFrame(
          np.vstack((age, sex, intercept)).T,
          columns=["age", "sex", "intercept"],
      )
      return design_matrix
  
imports: import os
  import numpy
  import pandas
  import nilearn
  from nilearn import datasets
  from nilearn.glm.first_level import FirstLevelModel, first_level_from_bids
  from nilearn.glm.first_level.design_matrix import make_first_level_design_matrix
  from nilearn.glm.second_level import SecondLevelModel
  from nilearn.image import resample_to_img
  from nilearn.interfaces.fsl import get_design_from_fslmat
  from nilearn.maskers import NiftiSpheresMasker
  from nilearn.reporting import make_glm_report
label_desc: Use image node_id 8 for calling a global function with example usage: _make_design_matrix_slm_oasis(oasis_dataset, n_subjects) and returns: design_matrix