Neuroscience
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Brain Imaging and Statistical Modelling

I work in the NeuroSpin brain research center, in the Parietal INRIA team and the Unicog INSERM team.

Spatial patterns of spontaneous activity

I develop algorithms and models for extracting salient and reproducible spatial features from the correlation structure of functional MRI images without using a paradigm, such as in resting-state studies. I focus on group models, opening the door to between-subject comparisons.

Spontaneous brain activity, recorded via fMRI, and displayed with Nipy and Mayavi

Group inference for functional connectivity

How to compare correlation structures to extract differences in the underlying graphical models that can explain the observations?

Finding from large correlation structures which edges can explain differences is an ill-posed problem. We are developing statistical models and machine learning tools to tackle this challenge.

Multivariate analysis of functional brain imaging

We apply machine-learning techniques for multivariate brain decoding: starting from brain activity data we find predictive features of behavior.

Papers in preparation: Total Variation regularization enhances regression-based brain activity prediction

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