no code implementations • 1 Feb 2021 • Francesco Conti, Gaetano Scarano, Stefania Colonnese
This paper introduces Multiscale Anisotropic Harmonic Filters (MAHFs) aimed at extracting signal variations over non-Euclidean domains, namely 2D-Manifolds and their discrete representations, such as meshes and 3D Point Clouds as well as graphs.
no code implementations • 21 Dec 2020 • Tiziana Cattai, Gaetano Scarano, Marie-Constance Corsi, Danielle S. Bassett, Fabrizio De Vico Fallani, Stefania Colonnese
Using our novel formulation of the J-divergence, we are able to quantify the distance between the FC networks in the motor imagery and resting states, as well as to understand the contribution of each Laplacian variable to the total J-divergence between two states.
no code implementations • 5 Dec 2019 • Tiziana Cattai, Stefania Colonnese, Marie-Constance Corsi, Danielle S. Bassett, Gaetano Scarano, Fabrizio De Vico Fallani
In the last decade, functional connectivity (FC) estimators have been increasingly explored based on their ability to capture synchronization between multivariate brain signals.