In the last decade, approach developed in the frame of complex network theory has presented very successful and popular tools for studying the structure andfunctioning of complex systems. A particularly attractive avenue in this context is the analysis of biological systems, since structural principles of complex networks have been identified at all scales of functioning of living organisms. In the present paper, we propose the construction of a complex network representation of a pancreatic islet. In this compact microorgan, under physiological conditions the release of the single most important anabolic hormone insulin is robustly controlled by an efficient cell-to-cell communication mediated by gap junctions. Here, we extract networks of insulin releasing beta-cells from experimentally measured time series data on calcium dynamics and from positional information obtained by confocal laser-scanning functional imaging of islets in acute pancreatic tissue slices. In particular,connectivity patterns are determined on the basis of correlations between calcium dynamics in the islet. The extracted networks are then scrutinized with conventional tools for network analysis, whereby particular importance is devoted to comparison of the network structure under low and high glucose levels, i.e. physiologically resting and stimulating conditions, respectively. We show that the cellular dynamics is more correlated under stimulation and that the networks obtained in both regimes display a differentorganization. The range of interactions among beta cells is significantly shorter in the case of a higher stimulation. Our results thus provide novel insights into the relationship between network topology and functional organization of pancreatic islets.
B.04 Guest lecture
COBISS.SI-ID: 512228664Lecture where we presented the results of Defense mechanisms of empathetic players in the spatial ultimatum game, Attila Szolnoki, Matjaž Perc and György Szabó, Phys. Rev. Lett. 109, 078701 (2012)
B.05 Guest lecturer at an institute/university
COBISS.SI-ID: 19123208