code: def _process_channel_eeg(cur_ch, elec):
      """Convert EEG channel from FieldTrip to MNE.
  
      Parameters
      ----------
      cur_ch: dict
          Channel specific dictionary to populate.
  
      elec: dict
          elec dict as loaded from the FieldTrip structure
  
      Returns
      -------
      cur_ch: dict
          The original dict (cur_ch) with the added information
      """
      all_labels = np.asanyarray(elec["label"])
      chan_idx_in_elec = np.where(all_labels == cur_ch["ch_name"])[0][0]
      position = np.squeeze(elec["chanpos"][chan_idx_in_elec, :])
      # chanunit = elec['chanunit'][chan_idx_in_elec]  # not used/needed yet
      position_unit = elec["unit"]
  
      position = position * _unit_dict[position_unit]
      cur_ch["loc"] = np.hstack((position, np.zeros((9,))))
      cur_ch["unit"] = FIFF.FIFF_UNIT_V
      cur_ch["kind"] = FIFF.FIFFV_EEG_CH
      cur_ch["coil_type"] = FIFF.FIFFV_COIL_EEG
      cur_ch["coord_frame"] = FIFF.FIFFV_COORD_HEAD
  
      return cur_ch
  
file_path: mne-python/mne/io/fieldtrip/utils.py
imports: import numpy
  from ..._fiff._digitization import DigPoint, _ensure_fiducials_head
  from ..._fiff.constants import FIFF
  from ..._fiff.meas_info import create_info
  from ..._fiff.pick import pick_info
  from ...transforms import rotation3d_align_z_axis
  from ...utils import _check_pandas_installed, warn
label_desc: Use image node_id 9 for calling a global function with example usage: _process_channel_eeg(cur_ch, elec) and returns: cur_ch