code: def _smooth(con, vcon, msk, sigma):
      """
      Integrate spatial uncertainty in standard space assuming that
      localization errors follow a zero-mean Gaussian distribution with
      axis-wise standard deviations `sigma` in voxel units. The expected
      Euclidean norm of registration errors is sqrt(NDIM) * sigma.
      """
      scon = _gaussian_filter(con, msk, sigma)
      svcon = _gaussian_filter(con**2, msk, sigma) - scon**2
      if vcon is not None:
          svcon += _gaussian_filter(vcon, msk, sigma)
      return scon, svcon
  
imports: import warnings
  from os.path import join
  import numpy
  import scipy.ndimage
  import scipy.stats
  from nibabel import io_orientation
  from ...None import save_image
  from ...core.image.image_spaces import make_xyz_image, xyz_affine
  from ..kernel_smooth import fwhm2sigma
  from ..registration import resample
  from ..statistics.bayesian_mixed_effects import two_level_glm
  from ..statistics.histogram import histogram
label_desc: Use image node_id 4 for calling a global function with example usage: _smooth(con, vcon, msk, sigma) and returns: scon,  svcon