Akrem Sellami has got a paper accepted at IJCNN 2020: Mapping individual differences in cortical architecture using multi-view representation learning

General overview of the proposed machine learning method.

They proposed a multi-view deep autoencoder model which allows combining the activation-and connectivity-based information respectively measured through these two fMRI protocols to identify markers of individual differences in the functional organization of the brain.

If you want to learn more about that, the full paper is available on the open archive HAL.

Akrem will make a 20 minutes talk.