class_docstr: Determines if stimuli are correlated with motion or intensity
  parameters.
  
  Currently this class supports an SPM generated design matrix and requires
  intensity parameters. This implies that one must run
  :ref:`ArtifactDetect <nipype.algorithms.rapidart.ArtifactDetect>`
  and :ref:`Level1Design <nipype.interfaces.spm.model.Level1Design>` prior to
  running this or provide an SPM.mat file and intensity parameters through
  some other means.
  
  Examples
  --------
  
  >>> sc = StimulusCorrelation()
  >>> sc.inputs.realignment_parameters = 'functional.par'
  >>> sc.inputs.intensity_values = 'functional.rms'
  >>> sc.inputs.spm_mat_file = 'SPM.mat'
  >>> sc.inputs.concatenated_design = False
  >>> sc.run() # doctest: +SKIP
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code: def _list_outputs(self):
      outputs = self._outputs().get()
      files = []
      for i, f in enumerate(self.inputs.realignment_parameters):
          files.insert(i, self._get_output_filenames(f, os.getcwd()))
      if files:
          outputs["stimcorr_files"] = files
      return outputs
  
imports: import os
  from copy import deepcopy
  from nibabel import load, funcs, Nifti1Image
  import numpy
  from ..interfaces.base import BaseInterface, traits, InputMultiPath, OutputMultiPath, TraitedSpec, File, BaseInterfaceInputSpec, isdefined
  from ..utils.filemanip import ensure_list, save_json, split_filename
  from ..utils.misc import find_indices, normalize_mc_params
  from ..None import logging, config
label_desc: Use image node_id 5 for calling the StimulusCorrelation obj's underlying member method code with example usage: obj._list_outputs() and returns: outputs