code: def two_runs_model(nb_cols_design_matrix):
      # Create two runs of data
      shapes, rk = [(7, 8, 9, 15), (7, 8, 9, 15)], nb_cols_design_matrix
      (
          mask,
          fmri_data,
          design_matrices,
      ) = generate_fake_fmri_data_and_design(
          shapes,
          rk,
      )
      # Rename two conditions in design matrices
      mapper = {
          design_matrices[0].columns[0]: "AAA",
          design_matrices[0].columns[1]: "BBB",
      }
      design_matrices[0] = design_matrices[0].rename(columns=mapper)
      mapper = {
          design_matrices[1].columns[0]: "AAA",
          design_matrices[1].columns[1]: "BBB",
      }
      design_matrices[1] = design_matrices[1].rename(columns=mapper)
  
      masker = NiftiMasker(mask)
      masker.fit()
  
      return FirstLevelModel(
          mask_img=None,
          minimize_memory=False,
      ).fit(
          fmri_data,
          design_matrices=design_matrices,
      )
  
imports: import json
  import os
  import numpy
  import pandas
  import pytest
  from nilearn._utils.data_gen import add_metadata_to_bids_dataset, create_fake_bids_dataset, generate_fake_fmri_data_and_design
  from nilearn.glm.first_level import FirstLevelModel
  from nilearn.glm.second_level import SecondLevelModel
  from nilearn.interfaces.bids import get_bids_files, parse_bids_filename, save_glm_to_bids
  from nilearn.interfaces.bids.query import _get_metadata_from_bids, infer_repetition_time_from_dataset, infer_slice_timing_start_time_from_dataset
  from nilearn.maskers import NiftiMasker
label_desc: Use image node_id 11 for calling a global function with example usage: two_runs_model(nb_cols_design_matrix) and returns: FirstLevelModel