fmri.sgroupICA: Spatial group ICA for fmri
In neuroconductor/fmri: Analysis of fMRI Experiments

Description Usage Arguments Details Value Author(s) References See Also

Combine ICA results from multiple runs or multiple subjects in group fMRI studies

1	fmri.sgroupICA(icaobjlist, thresh = 0.75, minsize=2)

`icaobjlist`	List of results obtained by function `fmri.sICA` for a series of fmri data sets (multiple runs or multiple subjects).
`thresh`	threshold for cluster aggregation. Needs to be in (0,1).
`minsize`	Minimal size of cluster to consider in IC aggregation. Needs to be larger than 1.

The fMRI time series need to be preprocessed and registered before thr ICA decomposition is performed.

The function employes a hierarchical clustering algorithm (complete linkage) on the combined set of spatial independent components obtained from the individual time series. A distance matrix is obtained from correlations of the independent component images. Aggregation of two components from the same fmri series is prevented in the algorithm.

An object of class ”fmrigroupICA” with components

`icacomp`	Mean IC's over cluster members for cluster of size larger or equal `minsize`
`size`	Size of selected clusters
`cl`	Number of selected clusters
`cluster`	Cluster membership corresponding to `thresh`.
`height`	Distance value at which the cluster was createt. Elements correspond to elements of cluster.
`hdm`	Object returned by function `hclust`.