A K-means multivariate approach for clustering independent components from magnetoencephalographic data.
Independent component analysis (ICA) is typically applied on functional magnetic resonance imaging, electroencephalographic and magnetoencephalographic (MEG) data due to its data-driven nature. In these applications, ICA needs to be extended from single to multi-session and multi-subject studies for interpreting and assigning a statistical significance at the group level. Here a novel strategy for analyzing MEG independent components (ICs) is presented, Multivariate Algorithm for Grouping MEG...Expand abstract
- Publisher copy:
- Copyright date:
Views and Downloads
If you are the owner of this record, you can report an update to it here: Report update to this record