fmri.sgroupICA {fmri} | R Documentation |
Spatial group ICA for fmri
Description
Combine ICA results from multiple runs or multiple subjects in group fMRI studies
Usage
fmri.sgroupICA(icaobjlist, thresh = 0.75, minsize=2)
Arguments
icaobjlist |
List of results obtained by function |
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. |
Details
The fMRI time series need to be preprocessed and registered before thr ICA decomposition is performed.
The function employs 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.
Value
An object of class ”fmrigroupICA
” with components
icacomp |
Mean IC's over cluster members for cluster of size larger
or equal |
size |
Size of selected clusters |
cl |
Number of selected clusters |
cluster |
Cluster membership corresponding to |
height |
Distance value at which the cluster was created. Elements correspond to elements of cluster. |
hdm |
Object returned by function |
Author(s)
Joerg Polzehl polzehl@wias-berlin.de
References
F. Esposito et al (2005) Independent component analysis of fMRI group studies by self-organizing clustering, Neuroimage, pp. 193-205.
See Also
fmri.sICA
, plot.fmrigroupICA
, hclust