COND

Describes tissue conductivity values

Initialization

• Python

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

• MATLAB

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

Attributes

• 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

  Warning

  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]

Examples

Note

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;