EOSC Future grant: Neuroimaging Working Group
Summary
The WG Neuroimaging data aims to create a community around the special case of reproducibility in the analysis of brain data. There is a growing awareness that scientific research processes are often very hard to replicate has led some to investigate the root causes of the so-called “reproducibility crisis”. Such appraisal has been prevalent in Psychology and Neuroscience, and typically highlights statistical issues, such as inadequate design or poor computational training. These problems are likely to get worse as the size of datasets grows, data becomes more widely shared, and complex techniques like machine learning are brought.
Reproducibility of neuroimaging data research is especially challenging, in both clinical and fundamental research. Workflows typically consist of a large number of processing steps, performed on a very heterogeneous set of equipment and infrastructures. This holds true for the whole data lifecycle: from the moment measurements are gathered in proprietary devices (magnetic resonance imaging scanners, electro-encephalography systems, etc) through preprocessing, analysis to annotation, curation, and finally deposited into open repositories for others to use in upstream research.
People and organisations
Key outputs:
Sustainable development goals
Primary
