Conference on Cognitive Computational Neuroscience

Anatomical and functional inter-subject variability in the cortex is a major impediment to computing meaningful insights from cohorts of individuals. Recent techniques leveraging optimal transport have been shown to build alignments which greatly improve inter-subject correlation between fMRI contrast maps. However, datasets used to train these alignments are very time- and money-consuming to acquire. We replicate these experiments with much more affordable training datasets and show that they can already help derive meaningful alignments and significantly increase correlation between subjects.