FT_SOURCEPLOT
Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_sourceplot”.
FT_SOURCEPLOT plots functional source reconstruction data on slices or on a surface, optionally as an overlay on anatomical MRI data, where statistical data can be used to determine the opacity of the mask. Input data comes from FT_SOURCEANALYSIS, FT_SOURCEGRANDAVERAGE or statistical values from FT_SOURCESTATISTICS. Use as ft_sourceplot(cfg, anatomical) ft_sourceplot(cfg, functional) ft_sourceplot(cfg, functional, anatomical) where the input data can contain either anatomical, functional or statistical data, or a combination of them. The input data can be in a 3-D volumetric representation or in a 2-D cortical sheet representation. If both anatomical and functional/statistical data is provided as input, they should be represented in the same coordinate system or interpolated on the same geometrical representation, e.g. using FT_SOURCEINTERPOLATE. The slice and ortho visualization plot the data in the input data voxel arrangement, i.e. the three ortho views are the 1st, 2nd and 3rd dimension of the 3-D data matrix, not of the head coordinate system. The specification of the coordinate for slice intersection is specified in head coordinates, i.e. relative to anatomical landmarks or fiducials and expressed in mm or cm. If you want the visualisation to be consistent with the head coordinate system, you can reslice the data using FT_VOLUMERESLICE. See http://bit.ly/1OkDlVF The configuration should contain: cfg.method = 'slice', plots the data on a number of slices in the same plane 'ortho', plots the data on three orthogonal slices 'surface', plots the data on a 3D brain surface 'glassbrain', plots a max-projection through the brain 'vertex', plots the grid points or vertices scaled according to the functional value 'cloud', plot the data as clouds, spheres, or points scaled according to the functional value cfg.anaparameter = string, field in data with the anatomical data (default = 'anatomy' if present in data) cfg.funparameter = string, field in data with the functional parameter of interest (default = []) cfg.maskparameter = string, field in the data to be used for opacity masking of fun data (default = []) If values are between 0 and 1, zero is fully transparant and one is fully opaque. If values in the field are not between 0 and 1 they will be scaled depending on the values of cfg.opacitymap and cfg.opacitylim (see below) You can use masking in several ways, f.i. - use outcome of statistics to show only the significant values and mask the insignificant NB see also cfg.opacitymap and cfg.opacitylim below - use the functional data itself as mask, the highest value (and/or lowest when negative) will be opaque and the value closest to zero transparent - Make your own field in the data with values between 0 and 1 to control opacity directly The following parameters can be used in all methods: cfg.downsample = downsampling for resolution reduction, integer value (default = 1) (orig: from surface) cfg.atlas = string, filename of atlas to use (default = []) see FT_READ_ATLAS for ROI masking (see 'masking' below) or for orthogonal plots (see method='ortho' below) cfg.visible = string, 'on' or 'off', whether figure will be visible (default = 'on') The following parameters can be used for the functional data: cfg.funcolormap = colormap for functional data, see COLORMAP (default = 'auto') 'auto', depends structure funparameter, or on funcolorlim - funparameter: only positive values, or funcolorlim:'zeromax' -> 'hot' - funparameter: only negative values, or funcolorlim:'minzero' -> 'cool' - funparameter: both pos and neg values, or funcolorlim:'maxabs' -> 'default' - funcolorlim: [min max] if min & max pos-> 'hot', neg-> 'cool', both-> 'default' cfg.funcolorlim = color range of the functional data (default = 'auto') [min max] 'maxabs', from -max(abs(funparameter)) to +max(abs(funparameter)) 'zeromax', from 0 to max(funparameter) 'minzero', from min(funparameter) to 0 'auto', if funparameter values are all positive: 'zeromax', all negative: 'minzero', both possitive and negative: 'maxabs' cfg.colorbar = 'yes' or 'no' (default = 'yes') The 'ortho' method can also plot time and/or frequency, the other methods can not. If your functional data has a time and/or frequency dimension, you can use cfg.latency = scalar or string, can be 'all', 'prestim', 'poststim', or [beg end], specify time range in seconds cfg.avgovertime = string, can be 'yes' or 'no' (default = 'no') cfg.frequency = scalar or string, can be 'all', or [beg end], specify frequency range in Hz cfg.avgoverfreq = string, can be 'yes' or 'no' (default = 'no') The following parameters can be used for the masking data: cfg.maskstyle = 'opacity', or 'colormix'. If 'opacity', low-level graphics opacity masking is applied, if 'colormix', the color data is explicitly expressed as a single RGB value, incorporating the opacitymask. Yields faster and more robust rendering in general. cfg.opacitymap = opacitymap for mask data, see ALPHAMAP (default = 'auto') 'auto', depends structure maskparameter, or on opacitylim - maskparameter: only positive values, or opacitylim:'zeromax' -> 'rampup' - maskparameter: only negative values, or opacitylim:'minzero' -> 'rampdown' - maskparameter: both pos and neg values, or opacitylim:'maxabs' -> 'vdown' - opacitylim: [min max] if min & max pos-> 'rampup', neg-> 'rampdown', both-> 'vdown' - NB. to use p-values use 'rampdown' to get lowest p-values opaque and highest transparent cfg.opacitylim = range of mask values to which opacitymap is scaled (default = 'auto') [min max] 'maxabs', from -max(abs(maskparameter)) to +max(abs(maskparameter)) 'zeromax', from 0 to max(abs(maskparameter)) 'minzero', from min(abs(maskparameter)) to 0 'auto', if maskparameter values are all positive: 'zeromax', all negative: 'minzero', both positive and negative: 'maxabs' cfg.roi = string or cell of strings, region(s) of interest from anatomical atlas (see cfg.atlas above) everything is masked except for ROI When cfg.method='ortho', three orthogonal slices will be rendered. You can click in any of the slices to update the display in the other two. You can also use the arrow keys on your keyboard to navigate in one-voxel steps. Note that the slices are along the first, second and third voxel dimension, which do not neccessarily correspond to the axes of the head coordinate system. See http://bit.ly/1OkDlVF The following parameters apply when cfg.method='ortho' cfg.location = location of cut, (default = 'auto') 'auto', 'center' if only anatomy, 'max' if functional data 'min' and 'max' position of min/max funparameter 'center' of the brain [x y z], coordinates in voxels or head, see cfg.locationcoordinates cfg.locationcoordinates = coordinate system used in cfg.location, 'head' or 'voxel' (default = 'head') 'head', headcoordinates as mm or cm 'voxel', voxelcoordinates as indices cfg.crosshair = 'yes' or 'no' (default = 'yes') cfg.axis = 'on' or 'off' (default = 'on') cfg.queryrange = number, in atlas voxels (default 3) cfg.clim = lower and upper anatomical MRI limits (default = [0 1]) When cfg.method='slice', a NxM montage with a large number of slices will be rendered. All slices are evenly spaced and along the same dimension. The following parameters apply for cfg.method='slice' cfg.nslices = number of slices, (default = 20) cfg.slicerange = range of slices in data, (default = 'auto') 'auto', full range of data [min max], coordinates of first and last slice in voxels cfg.slicedim = dimension to slice 1 (x-axis) 2(y-axis) 3(z-axis) (default = 3) cfg.title = string, title of the figure window When cfg.method='surface', the functional data will be rendered onto a cortical mesh (can be an inflated mesh). If the input source data contains a tri-field (i.e. a description of a mesh), no interpolation is needed. If the input source data does not contain a tri-field, an interpolation is performed onto a specified surface. Note that the coordinate system in which the surface is defined should be the same as the coordinate system that is represented in the pos-field. The following parameters apply to cfg.method='surface' when an interpolation is required cfg.surffile = string, file that contains the surface (default = 'surface_white_both.mat') 'surface_white_both.mat' contains a triangulation that corresponds with the SPM anatomical template in MNI coordinates cfg.surfinflated = string, file that contains the inflated surface (default = []) may require specifying a point-matching (uninflated) surffile cfg.surfdownsample = number (default = 1, i.e. no downsampling) cfg.projmethod = projection method, how functional volume data is projected onto surface 'nearest', 'project', 'sphere_avg', 'sphere_weighteddistance' cfg.projvec = vector (in mm) to allow different projections that are combined with the method specified in cfg.projcomb cfg.projcomb = 'mean', 'max', method to combine the different projections cfg.projweight = vector of weights for the different projections (default = 1) cfg.projthresh = implements thresholding on the surface level for example, 0.7 means 70% of maximum cfg.sphereradius = maximum distance from each voxel to the surface to be included in the sphere projection methods, expressed in mm cfg.distmat = precomputed distance matrix (default = []) The following parameters apply to cfg.method='surface' irrespective of whether an interpolation is required cfg.camlight = 'yes' or 'no' (default = 'yes') cfg.renderer = 'painters', 'zbuffer', ' opengl' or 'none' (default = 'opengl') note that when using opacity the OpenGL renderer is required. cfg.facecolor = [r g b] values or string, for example 'brain', 'cortex', 'skin', 'black', 'red', 'r', or an Nx3 or Nx1 array where N is the number of faces cfg.vertexcolor = [r g b] values or string, for example 'brain', 'cortex', 'skin', 'black', 'red', 'r', or an Nx3 or Nx1 array where N is the number of vertices cfg.edgecolor = [r g b] values or string, for example 'brain', 'cortex', 'skin', 'black', 'red', 'r' When cfg.method = 'cloud', the functional data will be rendered as as clouds (groups of points), spheres, or single points at each sensor position. These spheres or point clouds can either be viewed in 3D or as 2D slices. The 'anatomical' input may also consist of a single or multiple triangulated surface mesh(es) in an Nx1 cell-array to be plotted with the interpolated functional data (see FT_PLOT_CLOUD) The following parameters apply to cfg.method='elec' cfg.cloudtype = 'point' plots a single point at each sensor position 'cloud' (default) plots each a group of spherically arranged points at each sensor position 'surf' plots a single spherical surface mesh at each sensor position cfg.radius = scalar, maximum radius of cloud (default = 4) cfg.colorgrad = 'white' or a scalar (e.g. 1), degree to which color of points in cloud changes from its center cfg.slice = requires 'anatomical' as input (default = 'none') '2d', plots 2D slices through the cloud with an outline of the mesh '3d', draws an outline around the mesh at a particular slice cfg.ori = 'x', 'y', or 'z', specifies the orthogonal plane which will be plotted (default = 'y') cfg.slicepos = 'auto' or Nx1 vector specifying the position of the slice plane along the orientation axis (default = 'auto': chooses slice(s) with the most data) cfg.nslices = scalar, number of slices to plot if 'slicepos' = 'auto (default = 1) cfg.minspace = scalar, minimum spacing between slices if nslices>1 (default = 1) To facilitate data-handling and distributed computing you can use cfg.inputfile = ... If you specify this option the input data will be read from a *.mat file on disk. This mat files should contain only a single variable corresponding to the input structure. See also FT_SOURCEMOVIE, FT_SOURCEANALYSIS, FT_SOURCEGRANDAVERAGE, FT_SOURCESTATISTICS, FT_VOLUMELOOKUP, FT_READ_ATLAS, FT_READ_MRI
