UNIFIED ICA-SPM ANALYSIS OF FMRI EXPERIMENTS - Implementation of an ICA Graphical User Interface for the SPM Pipeline

Troels Bjerre, Jonas Henriksen, Carsten Haagen Nielsen, Peter Mondrup Rasmussen, Lars Kai Hansen, Kristoffer Hougaard Madsen

Abstract

We present a toolbox for exploratory analysis of functional magnetic resonance imaging (fMRI) data using independent component analysis (ICA) within the widely used SPM analysis pipeline. The toolbox enables dimensional reduction using principal component analysis, ICA using several different ICA algorithms, selection of the number of components using the Bayesian information criterion (BIC), visualization of ICA components, and extraction of components for subsequent analysis using the standard general linear model. We demonstrate how the toolbox is capable of identifying activity and nuisance effects in fMRI data from a visual experiment.

References

  1. Bell, A. and Sejnowski, T. (1995). An informationmaximization approach to blind separation and blind deconvolution. Neural Computation, 7:1129-1159.
  2. Cardoso, J.-F. (1999). High-order contrasts for independent component analysis. Neural Comput., 11(1):157-192.
  3. Correa, N., Adali, T., and Calhoun, V. (2007). Performance of blind source separation algorithms for fmri analysis using a group ica method. Magnetic Resonance Imaging, 25(5):684-694.
  4. Frackowiak, R., Friston, K., Frith, C., Dolan, R., Price, C., Zeki, S., Ashburner, J., and Penny, W. (2003). Human Brain Function. Academic Press, 2nd edition.
  5. Hansen, L., Larsen, J., and Kolenda, T. (2001a). Blind detection of independent dynamic components. Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP 7801). 2001 IEEE International Conference on, 5:3197-3200.
  6. Hansen, L., Larsen, J., and Kolenda, T. (2001b). Blind detection of independent dynamic components. Acoustics, Speech, and Signal Processing, 2001. Proceedings.(ICASSP'01). 2001 IEEE International Conference on, 5.
  7. Hansen, L., Larsen, J., Nielsen, F., Strother, S., Rostrup, E., Savoy, R., Lange, N., Sidtis, J., Svarer, C., and Paulson, O. (1999). Generalizable Patterns in Neuroimaging: How Many Principal Components? Neuroimage, 9(5):534-544.
  8. Højen-Sørensen, P., Winther, O., and Hansen, L. (2002). Analysis of functional neuroimages using ICA adaptive binary sources. Neurocomputing, 49(1):213-225.
  9. Hu, D., Yan, L., Liu, Y., Zhou, Z., Friston, K. J., Tan, C., and Wu, D. (2005). Unified spm-ica for fmri analysis. NeuroImage, 25:746-755.
  10. Hyvärinen, A. and Oja, E. (1997). A fast fixed-point algorithm for independent component analysis. Neural Computation, 9(7):1483-1492.
  11. Hyvärinen, A. and Oja, E. (2000). Independent component analysis: Algorithms and applications. Neural Networks, 13(4-5):411-430.
  12. Kolenda, T., Hansen, L., and Larsen, J. (2001). Signal detection using ICA: Application to chat room topic spotting. Third International Conference on Independent Component Analysis and Blind Source Separation, pages 540-545.
  13. Lund, T., Madsen, K., Sidaros, K., Luo, W., and Nichols, T. (2006). Non-white noise in fMRI: Does modelling have an impact? Neuroimage, 29(1):54-66.
  14. McKeown, M., Hansen, L., and Sejnowsk, T. (2003a). Independent component analysis of functional MRI: what is signal and what is noise? Current Opinion in Neurobiology, 13(5):620-629.
  15. McKeown, M., Hansen, L., and Sejnowsk, T. (2003b). Independent component analysis of functional mri: what is signal and what is noise? Current Opinion in Neurobiology, 13(5):620-629.
  16. McKeown, M., Makeig, S., Brown, G., Jung, T., Kindermann, S., Bell, A., and Sejnowski, T. (1998). Analysis of fmri data by blind separation into independent spatial components. Human Brain Mapping, 6(5):160- 188.
  17. Molgedey, L. and Schuster, H. (1994). Separation of independent signals using time-delayed correlations. Physical Review Letters, 72(23):3634-3637.
  18. Smith, L. (2002). A tutorial on Principal Components Analysis. Cornell University, USA, 51:52.
Download


Paper Citation


in Harvard Style

Bjerre T., Henriksen J., Haagen Nielsen C., Rasmussen P., Hansen L. and Hougaard Madsen K. (2009). UNIFIED ICA-SPM ANALYSIS OF FMRI EXPERIMENTS - Implementation of an ICA Graphical User Interface for the SPM Pipeline . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2009) ISBN 978-989-8111-65-4, pages 316-321. DOI: 10.5220/0001547803160321


in Bibtex Style

@conference{biosignals09,
author={Troels Bjerre and Jonas Henriksen and Carsten Haagen Nielsen and Peter Mondrup Rasmussen and Lars Kai Hansen and Kristoffer Hougaard Madsen},
title={UNIFIED ICA-SPM ANALYSIS OF FMRI EXPERIMENTS - Implementation of an ICA Graphical User Interface for the SPM Pipeline},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2009)},
year={2009},
pages={316-321},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001547803160321},
isbn={978-989-8111-65-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2009)
TI - UNIFIED ICA-SPM ANALYSIS OF FMRI EXPERIMENTS - Implementation of an ICA Graphical User Interface for the SPM Pipeline
SN - 978-989-8111-65-4
AU - Bjerre T.
AU - Henriksen J.
AU - Haagen Nielsen C.
AU - Rasmussen P.
AU - Hansen L.
AU - Hougaard Madsen K.
PY - 2009
SP - 316
EP - 321
DO - 10.5220/0001547803160321