Title :
Dynamical components analysis of fMRI data
Author :
Thirion, Bertrand ; Faugeras, Olivier
Author_Institution :
INRIA, France
Abstract :
We present a new multivariate analysis method for the analysis of fMRI data. This method tries to capture the deterministic structure present in the time series, using either an autoregressive scheme or the knowledge of the experimental paradigm, so that the interpretation of the spatiotemporal patterns is achieved in parallel with their detection. In the spatial domain, the components are made maximally independent through an ICA-like criterion. A global criterion is derived to express the model priors as well as the goodness of fit. The method is a priori adaptable to every sort of experimental conditions (block or event-related design). An experiment is presented on real data to show the potential of the method for the detection of signals, the analysis of their content as well as their localization.
Keywords :
biomedical MRI; independent component analysis; medical image processing; medical signal detection; spatiotemporal phenomena; time series; ICA-like criterion; autoregressive scheme; deterministic structure; dynamical components analysis; event-related design; experimental paradigm; fMRI data; global criterion; goodness of fit; localization; model priors; multivariate analysis method; real data; signal detection; spatial domain; spatiotemporal patterns; time series; Clustering methods; Covariance matrix; Data analysis; Decorrelation; Inference algorithms; Magnetic resonance imaging; Predictive models; Principal component analysis; Robots; Signal detection;
Conference_Titel :
Biomedical Imaging, 2002. Proceedings. 2002 IEEE International Symposium on
Print_ISBN :
0-7803-7584-X
DOI :
10.1109/ISBI.2002.1029410
