Towards reproducible neuroimaging across different analysis pipelines

When a change in analysis methods leads to different results, what does it mean for our research findings? In this presentation, I will discuss reproducibility in neuroimaging. Neuroimaging studies are characterized by a very large analysis space, and practitioners usually have to choose between different software, software versions, algorithms, parameters, etc. For many years, these choices have been regarded as implementation details, but it is becoming increasingly clear that the exact choices of analytical strategy can lead to different and sometimes contradictory results. I will review our recent efforts to better understand and manage the different sources of this analytical variability in neuroimaging.