code: def _make_design_matrix_for_bids_feature(
      data_dir, subject
  ):  # pragma: no cover
      fsl_design_matrix_path = os.path.join(
          data_dir,
          "derivatives",
          "task",
          subject,
          "stopsignal.feat",
          "design.mat",
      )
      design_matrix = get_design_from_fslmat(
          fsl_design_matrix_path, column_names=None
      )
  
      design_columns = [
          f"cond_{i:02d}" for i in range(len(design_matrix.columns))
      ]
      design_columns[0] = "Go"
      design_columns[4] = "StopSuccess"
      design_matrix.columns = design_columns
      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 4 for calling a global function with example usage: _make_design_matrix_for_bids_feature(data_dir, subject) and returns: design_matrix