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ISBI
2008
IEEE
14 years 6 months ago
Improved fMRI group studies based on spatially varying non-parametric BOLD signal modeling
Multi-subject analysis of functional Magnetic Resonance Imaging (fMRI) data relies on within-subject studies, which are usually conducted using a massively univariate approach. In...
Philippe Ciuciu, Thomas Vincent, Anne-Laure Fouque...
TMI
2010
175views more  TMI 2010»
12 years 12 months ago
Spatially Adaptive Mixture Modeling for Analysis of fMRI Time Series
Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In [1, 2...
Thomas Vincent, Laurent Risser, Philippe Ciuciu
ICASSP
2009
IEEE
14 years 10 hour ago
Fusion of fMRI, sMRI, and EEG data using canonical correlation analysis
Typically data acquired through imaging techniques such as functional magnetic resonance imaging (fMRI), structural MRI (sMRI), and electroencephalography (EEG) are analyzed separ...
Nicolle M. Correa, Yi-Ou Li, Tülay Adali, Vin...
ICASSP
2010
IEEE
13 years 3 months ago
Flexible complex ICA of fMRI data
Data-driven analysis methods, in particular independent component analysis (ICA) has proven quite useful for the analysis of functional magnetic imaging (fMRI) data. In addition, ...
Hualiang Li, Tülay Adali, Nicolle M. Correa, ...
ISBI
2004
IEEE
14 years 6 months ago
Nonlinear Dimension Reduction of fMRI Data: The Laplacian Embedding Approach
In this paper, we introduce the use of nonlinear dimension reduction for the analysis of functional neuroimaging datasets. Using a Laplacian Embedding approach, we show the power ...
Olivier D. Faugeras, Bertrand Thirion