code: def _load_global_signal(confounds_raw, global_signal):
      """Load the regressors derived from the global signal.
  
      Parameters
      ----------
      confounds_raw : pandas.DataFrame
          DataFrame of confounds.
  
      global_signal : str
          Global signal strategy to use. Options are "basic",
          "derivatives", "power2", or "full".
  
      Returns
      -------
      pandas.DataFrame
          DataFrame of global signal regressors.
  
      Raises
      ------
      MissingConfound
          When global signal regressors are not found, raise error as global
          signal is not a valid choice of strategy.
      """
      global_params = add_suffix(["global_signal"], global_signal)
      if check_params(confounds_raw, global_params):
          return confounds_raw[global_params]
      else:
          raise MissingConfound(keywords=["global_signal"])
  
file_path: nilearn/nilearn/interfaces/fmriprep/load_confounds_components.py
imports: import numpy
  import pandas
  from .load_confounds_compcor import find_compcor
  from .load_confounds_scrub import optimize_scrub
  from .load_confounds_utils import MissingConfound, add_suffix, check_params, find_confounds
label_desc: Use image node_id 4 for calling a global function with example usage: _load_global_signal(confounds_raw, global_signal) and returns: confounds_raw