no code implementations • 28 Mar 2023 • Giovanna Maria Dimitri, Simeon Spasov, Andrea Duggento, Luca Passamonti, Pietro Li`o, Nicola Toschi
As proof of concept, we test our architecture on the well characterized Human Connectome Project database demonstrating that our latent embeddings can be clustered into easily separable subject strata which, in turn, map to different phenotypical information which was not included in the embedding creation process.
2 code implementations • 27 Sep 2022 • Alexander Campbell, Antonio Giuliano Zippo, Luca Passamonti, Nicola Toschi, Pietro Lio
Graph neural networks (GNNs) have demonstrated success in learning representations of brain graphs derived from functional magnetic resonance imaging (fMRI) data.
1 code implementation • 29 Feb 2020 • Tiago Azevedo, Luca Passamonti, Pietro Liò, Nicola Toschi
The characterisation of the brain as a "connectome", in which the connections are represented by correlational values across timeseries and as summary measures derived from graph theory analyses, has been very popular in the last years.