172 citations · 247 across the 4 of their papers we have counts for
5 papers
FAASTA: A fast solver for total-variation regularization of ill-conditioned problems with application to brain imaging
Gaël Varoquaux, Michael Eickenberg, Elvis Dohmatob +1
The total variation (TV) penalty, as many other analysis-sparsity problems, does not lead to separable factors or a proximal operatorwith a closed-form expression, such as soft thr…
Machine Learning for Neuroimaging with Scikit-Learn
Alexandre Abraham, Fabian Pedregosa, Michael Eickenberg +6
Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g. multivariate…
Data-driven HRF estimation for encoding and decoding models
Fabian Pedregosa, Michael Eickenberg, Philippe Ciuciu +2
Despite the common usage of a canonical, data-independent, hemodynamic response function (HRF), it is known that the shape of the HRF varies across brain regions and subjects. This…
Second order scattering descriptors predict fMRI activity due to visual textures
Michael Eickenberg, Fabian Pedregosa, Senoussi Mehdi +2
Second layer scattering descriptors are known to provide good classification performance on natural quasi-stationary processes such as visual textures due to their sensitivity to h…
HRF estimation improves sensitivity of fMRI encoding and decoding models
Fabian Pedregosa, Michael Eickenberg, Bertrand Thirion +1
Extracting activation patterns from functional Magnetic Resonance Images (fMRI) datasets remains challenging in rapid-event designs due to the inherent delay of blood oxygen level-…