CSS/ITALY 2025

Session

Session 10

17 Sept 2025, 11:20

Centro Polifunzionale Studenti Università di Bari

170. Quantifying biases in reconstructed brain networks

V. D'Andrea

17/09/2025, 11:20

Brain network reconstruction from neuroimaging data is subject to sources of systematic bias. One can arise from the arbitrariness introduced by thresholding procedures used in typical structural and functional network reconstruction techniques. The produced connectivity matrices exhibit variable density, which has been shown to impact the evaluation of many graph metrics [1]. Additionally,...

171. Data-Driven Resilience Analysis of the Foggia Road Network under Targeted Bridge Attack Scenarios Using Complex Network Theory

N. Kheirkhahan

17/09/2025, 11:40

This research applies complex network theory to investigate the resilience of provincial road networks, focusing on Foggia Province in southern Italy. Foggia was selected due to its critical role in regional logistics and its vulnerability to disruptions caused by environmental hazards such as earthquakes. Road infrastructure resilience is essential for sustaining economic and social systems,...

172. Exploring the linkages between cancer incidence and socio-economic well-being with com- plex networks and machine learning

A. Lo Sasso

17/09/2025, 12:00

In recent years, network science predictive methods leveraging artificial intelligence have gained particular prominence in big data analysis. Among the various implementations of these tools, they have proven particularly useful for monitoring and predicting socioeconomic and health-related phenomena, uncovering intriguing and non-intuitive patterns [1]. In this way, a consensus began to...

173. Incorporating Structure of Interactions and Effective Learning in Random Neural Networks

L. Taffarello

17/09/2025, 12:20

The collective dynamics of complex systems such as neural circuits are shaped by how their units interact. Theoretical models of recurrent neural networks (RNNs) with random interactions have been investigated by dynamical mean field theory (DMFT) to derive fundamental properties of their dynamics such as the onset of chaos. However, the fully-interacting systems considered in previous studies...