Peter John Hellyer

The paper introduces an active learning approach to efficiently approximate multiverse analyses in neuroimaging, demonstrating its ability to identify optimal analysis pipelines for predicting participant ages.

This paper investigates how human brain network resources are optimised during learning complex tasks using self-ordered switching fMRI paradigms, finding that structured behaviour with low algorithmic complexity improves performance.