Claire Cury

This paper presents a multimodal dataset combining EEG and fMRI during a motor imagery neurofeedback task, enabling research on multi-modal data integration and neurofeedback methodologies.

The paper predicts bi-modal neurofeedback scores from EEG alone using a sparse regression model, showing improved correlation with combined fMRI-EEG sessions.

This paper introduces a diffeomorphic centroid method for shape analysis of large datasets, showing it achieves similar results to variational templates but with 70% faster computation.

The paper detects pre-symptomatic shape changes in the thalamus using spatiotemporal analysis of MRI scans from the GENFI study, finding differences five years before symptoms appear.