code: def get_first_level_dataset():
      """Heavier dataset (30 MO) for first-level analysis"""
      # define several paths
      url = "ftp://ftp.cea.fr/pub/dsv/madic/download/nipy"
      raw_fmri = os.path.join(DATA_DIR, "s12069_swaloc1_corr.nii.gz")
      paradigm = os.path.join(DATA_DIR, "localizer_paradigm.csv")
  
      # create DATA_DIR
      if not os.path.exists(DATA_DIR):
          os.makedirs(DATA_DIR)
          assert os.path.exists(DATA_DIR)
  
      # download mask_image if necessary
      if not os.path.exists(paradigm):
          print("Downloading mask image, this may take time")
          datafile = os.path.join(url, "localizer_paradigm.csv")
          fp = urlopen(datafile)
          local_file = open(paradigm, "wb")
          local_file.write(fp.read())
          local_file.flush()
          local_file.close()
  
      # download raw_fmri if necessary
      if not os.path.exists(raw_fmri):
          print("Downloading fmri image, this may take time")
          filename = "s12069_swaloc1_corr.nii.gz"
          datafile = os.path.join(url, filename)
          fp = urlopen(datafile)
          local_file = open(raw_fmri, "wb")
          local_file.write(fp.read())
          local_file.flush()
          local_file.close()
  
      return DATA_DIR
  
imports: import os
  import tarfile
  from nibabel.data import get_nipy_user_dir
label_desc: Use image node_id 2 for calling a global function with example usage: get_first_level_dataset() and returns: DATA_DIR