code: def _fetch_bids_data():  # pragma: no cover
      _, urls = datasets.func.fetch_openneuro_dataset_index()
  
      exclusion_patterns = [
          "*group*",
          "*phenotype*",
          "*mriqc*",
          "*parameter_plots*",
          "*physio_plots*",
          "*space-fsaverage*",
          "*space-T1w*",
          "*dwi*",
          "*beh*",
          "*task-bart*",
          "*task-rest*",
          "*task-scap*",
          "*task-task*",
      ]
      urls = datasets.func.select_from_index(
          urls, exclusion_filters=exclusion_patterns, n_subjects=1
      )
  
      data_dir, _ = datasets.func.fetch_openneuro_dataset(urls=urls)
      return data_dir
  
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 2 for calling a global function with example usage: _fetch_bids_data() and returns: data_dir