Abstract
In functional MRI (fMRI), analysis of multisubject data typically involves spatially normalizing (i.e. co-registering in a common standard space) all data sets and summarizing results in a single group activation map. This widely used approach does not explicitely account for between-subject anatomo-functional variability. Therefore, we propose a group effect analysis method which makes use of a multivariate model to select the main signal variations that are common to all subjects, while allowing final statistical inference on the individual scale. The normalization step is thus avoided and individual anatomo-functional features are preserved. The approach is evaluated by using simulated data and it is shown that sensitivity is drastically improved compared to more conventional individual analysis.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Büchel, C., Turner, R., Friston, K.: Lateral geniculate activations can be detected using intersubject averaging and fMRI. Magn. Reson. Med. 38, 691–694 (1997)
Price, C.J., Friston, K.: Cognitive conjunction: A new approach to brain activation experiments. NeuroImage 5, 261–270 (1997)
Holmes, A.P., Friston, K.J.: Generalisability, random effects & population inference. NeuroImage 7, S754 (1998)
Friston, K.J., Holmes, A.P., Price, C.J., Büchel, C., Worsley, K.J.: Multisubject fMRI studies and conjunction analysis. NeuroImage 10, 385–396 (1999)
Worsley, K.J., Aston, J., Petre, V., Duncan, G.H., Morales, F., Evans, A.C.: A general statistical analysis for fMRI data. NeuroImage 15, 1–15 (2002)
Talairach, J., Tournoux, P.: Co-planar stereotaxic atlas of the human brain. In: 3-Dimensional proportional system: an approach to cerebral imaging, Thieme, New York (1988)
Calhoun, V.D., Adali, T., Pearlson, G.D., Pekar, J.J.: A method for making group inferences from functional MRI data using Independent Component Analysis. Hum. Brain Mapp. 14, 140–151 (2001)
Svensén, M., Kruggel, F., Benali, H.: ICA of fMRI group study data. NeuroImage 16, 551–563 (2002)
Benali, H., Mattout, J., Pélégrini-Issac, M., Meusburger, F., Derpierre, O., Kherif, F., Poline, J.B., Burnod, Y.: Hierarchical multivariate group analysis of functional MRI data. In: Proceedings of the IEEE International Symposium on Biomedical Imaging, ISBI 2002, pp. 843–846 (2002)
Caussinus, H.: Models and uses of principal components analysis. In: de Leeuv, J. (ed.) Multidimensional data analysis, pp. 149–178. DSWO Press, Leiden (1986)
Mattout, J., Pélégrini-Issac, M., Garnero, L., Burnod, Y., Benali, H.: Multivariate PCA-based regression analysis of fMRI time series. NeuroImage 11, S586 (2000)
Fine, J., Pousse, A.: Assymptotic study of the multivariate functional model. Application to metric choice in principal component analysis. Statistics 23, 63–83 (1992)
Sijbers, J., den Dekker, A.J., Van Audekerke, J., Verhoye, M., Van Dyck, D.: Estimation of the noise in magnitude MR images. Magn. Reson. Med. 16, 87–90 (1998)
Velicer, W.F.: Determining the number of components from matrix of partial correlations. Psychometrika 41, 321–327 (1976)
Mardia, K.V., Kent, J.T., Bibby, J.M.: Multivariate Analysis. Academic Press, London (1979)
Metz, C.E.: Basic principles of ROC analysis. Semin. Nucl. Med. 8, 283–298 (1978)
Kruggel, F., Zysset, S., von Cramon, D.Y.: Nonlinear regression functional MRI data: an item-recognition task study. NeuroImage 11, 173–183 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Benali, H., Mattout, J., Pélégrini-Issac, M. (2003). Multivariate Group Effect Analysis in Functional Magnetic Resonance Imaging. In: Taylor, C., Noble, J.A. (eds) Information Processing in Medical Imaging. IPMI 2003. Lecture Notes in Computer Science, vol 2732. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45087-0_46
Download citation
DOI: https://doi.org/10.1007/978-3-540-45087-0_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40560-3
Online ISBN: 978-3-540-45087-0
eBook Packages: Springer Book Archive