5 papers
Mitigating analytical variability in fMRI results with style transfer
Elodie Germani, Camille Maumet, Elisa Fromont
We propose a novel approach to improve the reproducibility of neuroimaging results by converting statistic maps across different functional MRI pipelines. We make the assumption th…
Predicting Parkinson's disease trajectory using clinical and functional MRI features: a reproduction and replication study
Elodie Germani, Nikhil Baghwat, Mathieu Dugré +7
Parkinson's disease (PD) is a common neurodegenerative disorder with a poorly understood physiopathology and no established biomarkers for the diagnosis of early stages and for pre…
On the validity of fMRI studies with subject-level data processed through different pipelines
Elodie Germani, Xavier Rolland, Pierre Maurel +1
In recent years, the lack of reproducibility of research findings has become an important source of concerns in many scientific fields, including functional Magnetic Resonance Imag…
The HCP multi-pipeline dataset: an opportunity to investigate analytical variability in fMRI data analysis
Elodie Germani, Elisa Fromont, Pierre Maurel +1
Results of functional Magnetic Resonance Imaging (fMRI) studies can be impacted by many sources of variability including differences due to: the sampling of the participants, diffe…
Uncovering communities of pipelines in the task-fMRI analytical space
Elodie Germani, Elisa Fromont, Camille Maumet
Analytical workflows in functional magnetic resonance imaging are highly flexible with limited best practices as to how to choose a pipeline. While it has been shown that the use o…