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A Toolbox for Model-Free Analysis of fMRI Data

  • Conference paper
Independent Component Analysis and Signal Separation (ICA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4666))

Abstract

We introduce Model-free Toolbox (MFBOX), a Matlab toolbox for analyzing multivariate data sets in an explorative fashion. Its main focus lies on the analysis of functional Nuclear Magnetic Resonance Imaging (fMRI) data sets with various model-free or data-driven techniques. In this context, it can also be used as plugin for SPM5, a popular tool in regression-based fMRI analysis. The toolbox includes BSS algorithms based on various source models including ICA, spatiotemporal ICA, autodecorrelation and NMF. They can all be easily combined with higher-level analysis methods such as reliability analysis using projective clustering of the components, sliding time window analysis or hierarchical decomposition. As an example, we use MFBOX for the analysis of an fMRI experiment and present short comparisons with the SPM results. The MFBOX is freely available for download at http://mfbox.sf.net .

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Mike E. Davies Christopher J. James Samer A. Abdallah Mark D Plumbley

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© 2007 Springer-Verlag Berlin Heidelberg

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Gruber, P., Kohler, C., Theis, F.J. (2007). A Toolbox for Model-Free Analysis of fMRI Data. In: Davies, M.E., James, C.J., Abdallah, S.A., Plumbley, M.D. (eds) Independent Component Analysis and Signal Separation. ICA 2007. Lecture Notes in Computer Science, vol 4666. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74494-8_27

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  • DOI: https://doi.org/10.1007/978-3-540-74494-8_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74493-1

  • Online ISBN: 978-3-540-74494-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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