Describes tissue conductivity values


  • Python

    from simnibs import sim_struct
    s = sim_struct.SESSION()
    tdcs_list = s.add_tdcslist()
    gm_cond = tdcs_list.cond[1]


    s = sim_struct('SESSION');
    s.poslist{1} = sim_struct('TDCSLIST');
    gm_cond = s.poslist{1}.cond(2)


  • value: float

    • Description: Conductivity value, in S/m

  • Name: string (Python)/character array (MATLAB), optional

    • Description: Name of the tissue

  • distribution_type: ‘uniform’, ‘normal’, ‘beta’ or None/unset (Python/MATLAB), optional
    • Description: type of distribution for Uncertainty Quantification. Default: None/unset


    Setting this property will trigger a run of the UQ algorithm. Please see the tutorial on Uncertainty Quantification for more information

  • distribution_parameters: list/array of floats (Python/MATLAB)
    • Description: Sets the parameters for distribution defined in distribution_type.

      • if distribution_type is ‘uniform’: [min_value, max_value]

      • if distribution_type is ‘normal’: [mean, standard_deviation]

      • if distribution_type is ‘beta’: [p, q, min_value, max_value]



In this examples, we will consider a list/array of COND structures

  • Change the value of gray matter conductivity. See the Standard conductivity values.

    • Python

      # In Python, we have to take the cond struct
      # with the index tissue_number - 1
      cond[1].value = 0.2

    • MATLAB

      cond(2).value = 0.2;

  • Add the conductivity of 10 S/m and a name for a new tissue, labeled as 11

    • Python

      cond[10].name = 'Awesome tissue'
      cond[10].value = 10

    • MATLAB

      cond(11).name = 'Awesome tissue';
      cond(11).value = 10;