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Comparative Study
Model-free functional MRI analysis using topographic independent component analysis.
- Anke Meyer-Bäse, Oliver Lange, Axel Wismüller, and Helge Ritter.
- Department of Electrical and Computer Engineering, Florida State University, Tallahassee, FL 32310-6046, USA. amb@eng.fsu.edu
- Int J Neural Syst. 2004 Aug 1; 14 (4): 217-28.
AbstractData-driven fMRI analysis techniques include independent component analysis (ICA) and different types of clustering in the temporal domain. Since each of these methods has its particular strengths, it is natural to look for an approach that unifies Kohonen's self-organizing map and ICA. This is given by the topographic independent component analysis. While achieved by a slight modification of the ICA model, it can be at the same time used to define a topographic order (clusters) between the components, and thus has the usual computational advantages associated with topographic maps. In this contribution, we can show that when applied to fMRI analysis it outperforms FastICA.
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