Interpretable and integrative deep learning for discovering brain-behaviour associations

This record contains the data of the paper "Interpretable and integrative deep learning for discovering brain-behaviour associations". In this paper, we employ a digital avatar procedure as an interpretability module capable of reporting the relationships learned within a multi-view variational autoencoder. We integrate this procedure into a novel framework that utilises stability selection to identify meaningful and reproducible associations between brain imaging and behaviour.