FT_HEADMOVEMENT
Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_headmovement”.
FT_HEADMOVEMENT creates a raw data structure, or cell-array of datastructures containing the HLC-coil data, which have a grad structure that has the head position information incorporated. Use as data = ft_headmovement(cfg) where the configuration should contain cfg.dataset = string with the filename cfg.method = 'updatesens' (default), 'cluster', 'avgoverrpt', 'pertrial_cluster', 'pertrial' optional arguments are cfg.trl = empty (default), or Nx3 matrix with the trial definition, can be empty.see FT_DEFINETRIAL. If defined empty, the whole recording is used cfg.numclusters = number of segments with constant headposition in which to split the data (default = 10). This argument is used in some of the methods only (see below), and is used in a kmeans clustering scheme. If cfg.method = 'updatesens', the grad in the single output structure has a specification of the coils expanded as per the centroids of the position clusters. The balancing matrix is s a weighted concatenation of the original tra-matrix. This method requires cfg.numclusters to be specified If cfg.method = 'avgoverrpt', the grad in the single output structure has a specification of the coils according to the average head position across the specified samples. If cfg.method = 'cluster', the cell-array of output structures represent the epochs in which the head was considered to be positioned close to the corresponding kmeans-cluster's centroid. The corresponding grad-structure is specified according to this cluster's centroid. This method requires cfg.numclusters to be specified. If cfg.method = 'pertrial', the cell-array of output structures contains single trials, each trial with a trial-specific grad structure. Note that this is extremely memory inefficient with large numbers of trials, and probably an overkill. If cfg.method = 'pertrial_clusters', the cell-array of output structures contains sets of trials where the trial-specific head position was considered to be positioned close to the corresponding kmeans-cluster's centroid. The corresponding grad-structure is specified accordin to the cluster's centroid. This method requires cfg.numclusters to be specified. The updatesens method and related methods are described by Stolk et al., Online and offline tools for head movement compensation in MEG. NeuroImage, 2012. See also FT_REGRESSCONFOUND FT_REALTIME_HEADLOCALIZER