Region of interest based independent component analysis

Authors:
Ingo R. Keck;Jan Churan;Fabian J. Theis;Peter Gruber;Elmar W. Lang;Carlos G. Puntonet
Affiliations:
Institute of Biophysics, University of Regensburg, Regensburg, Germany;Generation Research Program, LMU Munich, Bad Tölz, Germany;Institute of Biophysics, University of Regensburg, Regensburg, Germany;Institute of Biophysics, University of Regensburg, Regensburg, Germany;Institute of Biophysics, University of Regensburg, Regensburg, Germany;Departamento ATC, Universidad de Granada/ESII, Granada, Spain
Venue:
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
Year:
2006

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Abstract

The over-complete case remains a difficult problem in the field of independent component analysis (ICA). In this article we combine a technique called “region of interest” (ROI) with a standard complete ICA. We show how to create a mask using ICA, then using the masked data for a second ICA. At the same time this method eliminates a commonly necessary model-based step in fMRI data analysis. We also demonstrate our approach on a real world fMRI data set example.