The Independent Component Analysis plugin (updated with BrainVoyager QX 1.7 and 2.0) is able to calculate and display "fingerprints" of independent components (De Martino et al., 2007). A fingerprint characterizes a component with respect to several spatial and temporal features making it possible to automatically classify components as related to BOLD responses, motion artefacts and so on. While at present fingerprints are only visualized, it is planned to offer automatic classification and sorting of components in future versions.
The snapshot above shows a plot reflecting a typical "BOLD" fingerprint. The graph also displays the names of the 11 features used to characterize independent components. After running the ICA plugin, fingerprint plots can be visualized by clicking the Fingerprint button in the Overlay Independent Components dialog as indicated in the snapshot below.
For the currently selected component, a fingerprint plot is produced as shown in the snapshot below. The fingerprint plot of the components does not show the names of the features, but there are arranged as shown in the plot above. Thus, if you want to know, which feature is reflected at a certain dimension (indicated by a "ray"), consult the plot above. If the IC Fingerprint dialog is open, switching to another component will automatically update the plot for the selected component (if Single selection mode is turned on).
De Martino F, Gentile F, Esposito F, Balsi M, Di Salle F, Goebel R, Formisano E. (2007). Classification of fMRI independent components using IC-fingerprints and support vector machine classifiers. Neuroimage, 34, 177-194.
Copyright © 2020 Rainer Goebel. All rights reserved.