Berlin 2024 – scientific programme
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SOE: Fachverband Physik sozio-ökonomischer Systeme
SOE 7: Poster
SOE 7.14: Poster
Monday, March 18, 2024, 18:00–20:30, Poster D
Information parity: a measure to quantify the influence of nodes in a network — Aline Viol1 and •Philipp Hövel2 — 1Scuola Internazionale Superiore di Studi Avanzati di Trieste (SISSA), Italy — 2Saarland University, Germany
A growing interest in complex networks theory results in an ongoing demand for analytical tools. In order to quantify the functional, statistical symmetries between nodes in a complex network, we propose information parity as an insightful measure. Unlike the usual approach to quantitative network analysis that considers only local or global scales, information parity instead quantifies pairwise statistical similarities over the entire network structure. Based on the statistics of geodesic distances, information parity assesses how similarly a pair of nodes can influence and be influenced by the network.
Relating to neuroscience, for instance, we find an increase in the average information parity on brain networks of individuals under psychedelic influences. Notably, the information parity between regions from the limbic system and frontal cortex is consistently higher for all the individuals while under the psychedelic influence. These findings suggest that the resemblance of statistical influences between pair of brain regions activities tends to increase under Ayahuasca effects. This could be interpreted as a mechanism to maintain the network functional resilience.
[1] A. Viol et al. J. Phys. Complexity 4, 01LT02 (2023).
[2] A. Viol et al. Physica A 561, 125233 (2021).
Keywords: complex networks; centrality measure; neuroscience; information parity