How Differences in Processing Reliability Can Hinder Advancement in Neuroimaging

Examining how cross-tool differences can distort our ability to detect individual variations, and advance the field.

When fields lack consensus standards and ground truths for their analytic methods, reproducibility tends to be more of an ideal than a reality. Such has been the case for functional neuroimaging, where there exists a sprawling space of tools from which scientists can construct processing pipelines and draw interpretations. We provide a critical evaluation of the impact of differences observed in results across five independently developed functional MRI minimal preprocessing pipelines. We show that even when handling the same exact data, inter-pipeline agreement was only moderate, with the specific steps that contribute to the lack of agreement varying across pipeline comparisons.

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