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» An fMRI Activation Method Using Complex Data
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ISBI
2004
IEEE
15 years 10 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
TMI
2008
136views more  TMI 2008»
14 years 9 months ago
Classification of fMRI Time Series in a Low-Dimensional Subspace With a Spatial Prior
We propose a new method for detecting activation in functional magnetic resonance imaging (fMRI) data. We project the fMRI time series on a low-dimensional subspace spanned by wave...
François G. Meyer, Xilin Shen
MICCAI
2009
Springer
15 years 10 months ago
Nonparametric Mean Shift Functional Detection in the Functional Space for Task and Resting-state fMRI
In functional Magnetic Resonance Imaging (fMRI) data analysis, normalization of time series is an important and sometimes necessary preprocessing step in many widely used methods. ...
Jian Cheng, Feng Shi, Kun Wang, Ming Song, Jiefeng...
TMI
2010
175views more  TMI 2010»
14 years 4 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
NIPS
2007
14 years 11 months ago
Locality and low-dimensions in the prediction of natural experience from fMRI
Functional Magnetic Resonance Imaging (fMRI) provides dynamical access into the complex functioning of the human brain, detailing the hemodynamic activity of thousands of voxels d...
Francois Meyer, Greg Stephens