Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_compute_leadfield”.

FT_COMPUTE_LEADFIELD computes a forward solution for a dipole in a a volume conductor model. The forward solution is expressed as the leadfield matrix (Nchan*3), where each column corresponds with the potential or field distributions on all sensors for one of the x,y,z-orientations of the dipole. Use as [lf] = ft_compute_leadfield(dippos, sens, headmodel, ...) with input arguments dippos = position dipole (1*3 or Ndip*3) sens = structure with gradiometer or electrode definition headmodel = structure with volume conductor definition The headmodel represents a volume conductor model, its contents depend on the type of model. The sens structure represents a sensor array, i.e. EEG electrodes or MEG gradiometers. It is possible to compute a simultaneous forward solution for EEG and MEG by specifying sens and grad as two cell-arrays, e.g. sens = {senseeg, sensmeg} headmodel = {voleeg, volmeg} This results in the computation of the leadfield of the first element of sens and headmodel, followed by the second, etc. The leadfields of the different imaging modalities are concatenated. Additional input arguments can be specified as key-value pairs, supported optional arguments are 'reducerank' = 'no' or number 'normalize' = 'no', 'yes' or 'column' 'normalizeparam' = parameter for depth normalization (default = 0.5) 'weight' = number or 1xN vector, weight for each dipole position (default = 1) 'backproject' = 'yes' (default) or 'no', in the case of a rank reduction this parameter determines whether the result will be backprojected onto the original subspace The leadfield weight may be used to specify a (normalized) corresponding surface area for each dipole, e.g. when the dipoles represent a folded cortical surface with varying triangle size. Depending on the specific input arguments for the sensor and volume, this function will select the appropriate low-level EEG or MEG forward model. The leadfield matrix for EEG will have an average reference over all the electrodes. The supported forward solutions for MEG are single sphere (Cuffin and Cohen, 1977) multiple spheres with one sphere per channel (Huang et al, 1999) realistic single shell using superposition of basis functions (Nolte, 2003) leadfield interpolation using a precomputed grid boundary element method (BEM) The supported forward solutions for EEG are single sphere multiple concentric spheres (up to 4 spheres) leadfield interpolation using a precomputed grid boundary element method (BEM) See also FT_PREPARE_VOL_SENS, FT_HEADMODEL_ASA, FT_HEADMODEL_BEMCP, FT_HEADMODEL_CONCENTRICSPHERES, FT_HEADMODEL_DIPOLI, FT_HEADMODEL_HALFSPACE, FT_HEADMODEL_INFINITE, FT_HEADMODEL_LOCALSPHERES, FT_HEADMODEL_OPENMEEG, FT_HEADMODEL_SINGLESHELL, FT_HEADMODEL_SINGLESPHERE, FT_HEADMODEL_HALFSPACE

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