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reference:ft_dipolefitting [2018/08/23 14:43] (current)
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 +=====  FT_DIPOLEFITTING =====
 +Note that this reference documentation is identical to the help that is displayed in MATLAB when you type "help ft_dipolefitting"​.
 +  <a href=/​reference/​ft_dipolefitting><​font color=green>​FT_DIPOLEFITTING</​font></​a>​ perform grid search and non-linear fit with one or multiple
 +  dipoles and try to find the location where the dipole model is best able
 +  to explain the measured EEG or MEG topography.
 +  This function will initially scan the whole brain with a single dipole on
 +  a regular coarse grid, and subsequently start at the most optimal location
 +  with a non-linear search. Alternatively you can specify the initial
 +  location of the dipole(s) and the non-linear search will start from there.
 +  Use as
 +    [source] = ft_dipolefitting(cfg,​ data)
 +  The configuration has the following general fields
 +    cfg.numdipoles ​ = number, default is 1
 +    cfg.symmetry ​   = '​x',​ '​y'​ or '​z'​ symmetry for two dipoles, can be empty (default = [])
 +    cfg.channel ​    = Nx1 cell-array with selection of channels (default = '​all'​),​
 +                      see <a href=/​reference/​ft_channelselection><​font color=green>​FT_CHANNELSELECTION</​font></​a>​ for details
 +    cfg.gridsearch ​ = '​yes'​ or '​no',​ perform global search for initial
 +                      guess for the dipole parameters (default = '​yes'​)
 +    cfg.nonlinear ​  = '​yes'​ or '​no',​ perform nonlinear search for optimal
 +                      dipole parameters (default = '​yes'​)
 +  If you start with a grid search, the complete grid with dipole
 +  positions and optionally precomputed leadfields should be specified
 +    cfg.grid ​           = structure, see <a href=/​reference/​ft_prepare_sourcemodel><​font color=green>​FT_PREPARE_SOURCEMODEL</​font></​a>​ or <a href=/​reference/​ft_prepare_leadfield><​font color=green>​FT_PREPARE_LEADFIELD</​font></​a>​
 +  The positions of the dipoles can be specified as a regular 3-D
 +  grid that is aligned with the axes of the head coordinate system
 +    cfg.grid.xgrid ​     = vector (e.g. -20:1:20) or '​auto'​ (default = '​auto'​)
 +    cfg.grid.ygrid ​     = vector (e.g. -20:1:20) or '​auto'​ (default = '​auto'​)
 +    cfg.grid.zgrid ​     = vector (e.g.   ​0:​1:​20) or '​auto'​ (default = '​auto'​)
 +    cfg.grid.resolution = number (e.g. 1 cm) for automatic grid generation
 +    cfg.grid.inside ​    = N*1 vector with boolean value whether grid point is inside brain (optional)
 +    cfg.grid.dim ​       = [Nx Ny Nz] vector with dimensions in case of 3-D grid (optional)
 +  If the source model destribes a triangulated cortical sheet, it is described as
 +    cfg.grid.pos ​       = N*3 matrix with the vertex positions of the cortical sheet
 +    cfg.grid.tri ​       = M*3 matrix that describes the triangles connecting the vertices
 +  Alternatively the position of a few dipoles at locations of interest can be
 +  specified, for example obtained from an anatomical or functional MRI
 +    cfg.grid.pos ​       = N*3 matrix with position of each source
 +  If you do not start with a grid search, you have to give a starting location
 +  for the nonlinear search
 +    cfg.dip.pos ​    = initial dipole position, matrix of Ndipoles x 3
 +  The conventional approach is to fit dipoles to event-related averages, which
 +  within FieldTrip can be obtained from the <a href=/​reference/​ft_timelockanalysis><​font color=green>​FT_TIMELOCKANALYSIS</​font></​a>​ or from
 +  the <a href=/​reference/​ft_timelockgrandaverage><​font color=green>​FT_TIMELOCKGRANDAVERAGE</​font></​a>​ function. This has the additional options
 +    cfg.latency ​    = [begin end] in seconds or '​all'​ (default = '​all'​)
 +    cfg.model ​      = '​moving'​ or '​regional'​
 +  A moving dipole model has a different position (and orientation) for each
 +  timepoint, or for each component. A regional dipole model has the same
 +  position for each timepoint or component, and a different orientation.
 +  You can also fit dipoles to the spatial topographies of an independent
 +  component analysis, obtained from the <a href=/​reference/​ft_componentanalysis><​font color=green>​FT_COMPONENTANALYSIS</​font></​a>​ function.
 +  This has the additional options
 +    cfg.component ​  = array with numbers (can be empty -&gt; all)
 +  You can also fit dipoles to the spatial topographies that are present
 +  in the data in the frequency domain, which can be obtained using the
 +  <a href=/​reference/​ft_freqanalysis><​font color=green>​FT_FREQANALYSIS</​font></​a>​ function. This has the additional options
 +    cfg.frequency ​  = single number (in Hz)
 +  Low level details of the fitting can be specified in the cfg.dipfit structure
 +    cfg.dipfit.display ​ = level of display, can be '​off',​ '​iter',​ '​notify'​ or '​final'​ (default = '​iter'​)
 +    cfg.dipfit.optimfun = function to use, can be '​fminsearch'​ or '​fminunc'​ (default is determined automatic)
 +    cfg.dipfit.maxiter ​ = maximum number of function evaluations allowed (default depends on the optimfun)
 +  Optionally, you can modify the leadfields by reducing the rank, i.e. remove the weakest orientation
 +    cfg.reducerank ​     = '​no',​ or number (default = 3 for EEG, 2 for MEG)
 +  The volume conduction model of the head should be specified as
 +    cfg.headmodel ​    = structure with volume conduction model, see <a href=/​reference/​ft_prepare_headmodel><​font color=green>​FT_PREPARE_HEADMODEL</​font></​a>​
 +  The EEG or MEG sensor positions can be present in the data or can be specified as
 +    cfg.elec ​         = structure with electrode positions, see <a href=/​reference/​ft_datatype_sens><​font color=green>​FT_DATATYPE_SENS</​font></​a>​
 +    cfg.grad ​         = structure with gradiometer definition, see <a href=/​reference/​ft_datatype_sens><​font color=green>​FT_DATATYPE_SENS</​font></​a>​
 +    cfg.elecfile ​     = name of file containing the electrode positions, see <a href=/​reference/​ft_read_sens><​font color=green>​FT_READ_SENS</​font></​a>​
 +    cfg.gradfile ​     = name of file containing the gradiometer definition, see <a href=/​reference/​ft_read_sens><​font color=green>​FT_READ_SENS</​font></​a>​
 +  To facilitate data-handling and distributed computing you can use
 +    cfg.inputfile ​  ​= ​ ...
 +    cfg.outputfile ​ =  ...
 +  If you specify one of these (or both) the input data will be read from a *.mat
 +  file on disk and/or the output data will be written to a *.mat file. These mat
 +  files should contain only a single variable, corresponding with the
 +  input/​output structure.
 +  See also <a href=/​reference/​ft_sourceanalysis><​font color=green>​FT_SOURCEANALYSIS</​font></​a>,​ <a href=/​reference/​ft_prepare_leadfield><​font color=green>​FT_PREPARE_LEADFIELD</​font></​a>,​ <a href=/​reference/​ft_prepare_headmodel><​font color=green>​FT_PREPARE_HEADMODEL</​font></​a>​