TDCSDistributedOptimize

TDCS optimization problem with a distributed target defined in a NIfTI file.

Initialization

• Python

  from simnibs import opt_struct
  opt = opt_struct.TDCSDistributedOptimize()
  

• MATLAB

  opt = opt_struct('TDCSDistributedOptimize');
  

Attributes

• leadfield_hdf: string (Python)/character array (MATLAB)

  • Description: Name of HDF5 file with leadfield (see TDCSLEADFIELD and also the first part of TDCS Optimization)

  • Example: Python/MATLAB

  opt.leadfield_hdf = 'tdcs_leadfield/ernie_leadfield_EEG10-10_UI_Jurak_2007.hdf5'
  

• name: string (Python)/character array (MATLAB)

  • Desctiption: Name of the optimization problem. Gives the path and the prefix to the output files

  • Example: Python/MATLAB

    To have the output files from the optimization in the tdcs_leadfield/ folder and the motor_cortex prefix

  opt.name = 'tdcs_leadfield/motor_cortex'
  

• target_image: str

  • Description: Image to be emulated with the optimization

  • Example: Python/MATLAB

    Suppose we have a T-map representing a functional network called T_map.nii.gz

  opt.target_image = 'T_map.nii.gz'
  

• mni_space: bool, optional

  • Descrption: Wether the target_image is in MNI space.

  • Default: True

• subpath: str, optional

  • Descrption: Path to the subject m2m_SubID folder. Needed if mni_space=True.

  • Example: Python/MATLAB

  opt.subpath = 'path/to/m2m_ernie'
  

• intensity: float, optional

  • Description: Target field intensity. The larger the value, the more the optimization will hit the target network, but at the cost at having higher fields outside of it. Corresponds to \(E_0\) in (Ruffini et al., 2014)

  • Default: 0.2

• min_img_value: float ≥ 0, optional

  • Descrption: minimum image value to be considered for optimization. All image values below it are set to zero. Corresponds to \(T_{min}\) in (Ruffini et al., 2014)

  • Default: 0

• open_in_gmsh: bool, optional

  • Descrption: Whether to open the result in Gmsh after the calculations.

  • Default: True

• max_total_current: float, optional

  • Description: Maximum total injected current, in A

  • Default: 2e-3

• max_individual_current: float, optional

  • Description: Maximum current injected in each electrode, in A

  • Default: 1e-3

• max_active_electrodes: int, optional

  • Description: Maximum number of active electrodes. Leave empty if no maximum number of electrodes

  • Default: No maximum