L
Leonardo Angelini
Researcher at Istituto Nazionale di Fisica Nucleare
Publications - 32
Citations - 422
Leonardo Angelini is an academic researcher from Istituto Nazionale di Fisica Nucleare. The author has contributed to research in topics: Ising model & Cluster analysis. The author has an hindex of 10, co-authored 32 publications receiving 369 citations. Previous affiliations of Leonardo Angelini include University of Bari.
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Journal ArticleDOI
Identification of network modules by optimization of ratio association.
Leonardo Angelini,Stefano Boccaletti,Daniele Marinazzo,Mario Pellicoro,Sebastiano Stramaglia +4 more
TL;DR: This work introduces a novel method for identifying the modular structures of a network based on the maximization of an objective function: the ratio association, and develops an efficient optimization algorithm,based on the deterministic annealing scheme.
Journal ArticleDOI
Synergetic and Redundant Information Flow Detected by Unnormalized Granger Causality: Application to Resting State fMRI
Sebastiano Stramaglia,Leonardo Angelini,Guo-Rong Wu,Jesus M. Cortes,Luca Faes,Daniele Marinazzo +5 more
TL;DR: The proposed approach to resting state functional magnetic resonance imaging data from the Human Connectome Project shows that redundant pairs of regions arise mainly due to space contiguity and interhemispheric symmetry, while synergy occurs mainly between nonhomologous Pair of regions in opposite hemispheres.
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Ising model with conserved magnetization on the human connectome: Implications on the relation structure-function in wakefulness and anesthesia
Sebastiano Stramaglia,M. Pellicoro,Leonardo Angelini,Enrico Amico,Hannelore Aerts,Jesus M. Cortes,Steven Laureys,Daniele Marinazzo +7 more
TL;DR: It is confirmed that brain dynamics under anesthesia shows a departure from criticality and could open the way to novel perspectives when the conserved magnetization is interpreted in terms of a homeostatic principle imposed to neural activity.
Journal ArticleDOI
Clustering data by inhomogeneous chaotic map lattices.
TL;DR: A new approach to clustering, based on the physical properties of inhomogeneous coupled chaotic maps, is presented, which serves to partition the data set in clusters without prior assumptions about the structure of the underlying distribution of the data.
Journal ArticleDOI
Conserved Ising Model on the Human Connectome
Sebastiano Stramaglia,Mario Pellicoro,Leonardo Angelini,Enrico Amico,Hannelore Aerts,Jesus M. Cortes,Steven Laureys,Daniele Marinazzo +7 more
TL;DR: It is confirmed that brain dynamics under anesthesia shows a departure from criticality and could open the way to novel perspectives when the conserved magnetization is interpreted in terms of an homeostatic principle imposed to neural activity.