Abstract
We discuss methods for analyzing fMRI data, stimulus-based such as baseline substraction and correlation analysis versus stimulus- independent methods such as Principal Component Analysis (PCA) and Independent Component Analysis (ICA) with respect to their capabil- ities of separating noise sources from functional activity. The methods are applied to a finger tapping fMRI experiment and it is shown that the stimulus-independent methods in addition to the extraction of the stimulus can reveal several non-stimulus related influences such as head movements or breathing.
This is a preview of subscription content, log in via an institution to check access.
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
J.F. Cardoso, A. Souloumiac, 1993, Blind Beamforming for Non Gaussian Signals, IEE-Proceedings-F, 140,No 6, 362–370
S. Dodel, J.M. Herrmann, T. Geisel, 2000, Comparison of Temporal and Spatial ICA in fMRI Data Analysis, Proc. ICA 2000, Helsinki, Finland, 543–547
J. Frahm, 1999, Magnetic Resonance Functional Neuroimaging: New Insights into the Human Brain, Current Science 76, 735–743
McKeown MJ. Sejnowski TJ, 1998, Independent Component Analysis of fMRI Data-Examining the Assumptions, Human Brain Mapping 6(5-6), 368–372
P. McCullagh, 1987, Tensor Methods in Statistics, Chapman and Hall, New York
W.H. Press, 1994, Numerical recipes in C, Cambridge Univ. Press
A. Stuart, K. Ord, 1994, Kendall’s Advanced Theory of Statistics, Vol. 1 Distribution theory, Halsted Press
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Dodel, S., Herrmann, J.M., Geisel, T. (2001). Stimulus-Independent Data Analysis for fMRI. In: Wermter, S., Austin, J., Willshaw, D. (eds) Emergent Neural Computational Architectures Based on Neuroscience. Lecture Notes in Computer Science(), vol 2036. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44597-8_3
Download citation
DOI: https://doi.org/10.1007/3-540-44597-8_3
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42363-8
Online ISBN: 978-3-540-44597-5
eBook Packages: Springer Book Archive