def METHOD_NAME(src: dict, normals: Union[dict, None] = None):
    """Create a dictionary with source model information which can be used with
    FieldTrip.
    PARAMETERS
    ----------
    src : dict
        Dictionary with entries `lh` and `rh` each being a
    normals : dict
    RETURNS
    -------
    sourcemodel : dict
        Dictionary with source model information.
    """
    hemi2fieldtrip = dict(lh="CORTEX_LEFT", rh="CORTEX_RIGHT")
    # Construct a composite triangulation for both hemispheres
    cortex = src["lh"].join_mesh(src["rh"])
    pos = cortex.nodes.node_coord
    # Msh class already uses 1-indexing (!) so no need to modify
    tri = cortex.elm.node_number_list[:, :3]
    # All sources are valid
    inside = np.ones(cortex.nodes.nr, dtype=bool)[:, None]
    # ft_read_headshape outputs this structure
    brainstructure = np.concatenate(
        [np.full(src[h].nodes.nr, i) for i, h in enumerate(src, start=1)]
    )
    brainstructurelabel = np.stack([hemi2fieldtrip[h] for h in src]).astype(object)
    sourcemodel = dict(
        pos=pos,
        tri=tri,
        unit="mm",
        inside=inside,
        brainstructure=brainstructure,
        brainstructurelabel=brainstructurelabel,
    )
    if normals:
        sourcemodel["normals"] = np.concatenate([normals[h] for h in src])
    return sourcemodel