University of Maribor

About: University of Maribor is a education organization based out in Maribor, Slovenia. It is known for research contribution in the topics: Population & KEKB. The organization has 3987 authors who have published 13077 publications receiving 258339 citations. The organization is also known as: Univerza v Mariboru.

Evolutionary dynamics of higher-order interactions in social networks

Abstract: We live and cooperate in networks. However, links in networks only allow for pairwise interactions, thus making the framework suitable for dyadic games, but not for games that are played in groups of more than two players. Here, we study the evolutionary dynamics of a public goods game in social systems with higher-order interactions. First, we show that the game on uniform hypergraphs corresponds to the replicator dynamics in the well-mixed limit, providing a formal theoretical foundation to study cooperation in networked groups. Secondly, we unveil how the presence of hubs and the coexistence of interactions in groups of different sizes affects the evolution of cooperation. Finally, we apply the proposed framework to extract the actual dependence of the synergy factor on the size of a group from real-world collaboration data in science and technology. Our work provides a way to implement informed actions to boost cooperation in social groups.

Characterization of Human Motor Units From Surface EMG Decomposition

Abstract: Motor units are the smallest functional units of our movements. The study of their activation provides a window into the mechanisms of neural control of movement in humans. The classic methods for motor unit investigations date to several decades ago. They are based on invasive recordings with selective needle or wire electrodes. Conversely, the noninvasive (surface) EMG has been commonly processed as an interference signal, with the extraction of its global characteristics, e.g., amplitude. These characteristics, however, are only crudely associated to the underlying motor unit activities. In the last decade, methods have been proposed for reliably extracting individual motor unit activities from the interference surface EMG signal. We describe these methods in this review, with a focus on blind source separation (BSS) and techniques used on decomposed EMG signals. For example, from the motor unit discharge timings, information can be extracted regarding the synaptic input received by the corresponding motor neurons. In reviewing these methods, we also provide examples of applications in representative conditions, such as pathological tremor. In conclusion, we provide an overview of processing methods of the surface EMG signal that allow a reliable characterization of individual motor units in vivo in humans.

Measurement of azimuthal asymmetries in inclusive production of hadron pairs in e + e - annihilation at s=10.58GeV

Abstract: The Collins effect connects transverse quark spin with a measurable azimuthal asymmetry in the yield of hadronic fragments around the quark's momentum vector. Using two different reconstruction methods we measure statistically significant azimuthal asymmetries for charged pion pairs in e+e- annihilation at center-of-mass energies of 10.52 GeV and 10.58 GeV, which can be attributed to the fragmentation of primordial quarks with transverse spin components. The measurement was performed using a data set of 547fb-1 collected by the Belle detector at KEKB improving the statistics of the previously published results by nearly a factor of 20. © 2008 The American Physical Society.

Spatial decoherence induced by small-world connectivity in excitable media

Abstract: We study effects of different network topologies on the noise-induced pattern formation in a two-dimensional model of excitable media with FitzHugh–Nagumo local dynamics. In particular, we show that the introduction of long-range couplings induces decoherence of otherwise coherent noise-induced spatial patterns that can be observed by regular connectivity of spatial units. Importantly, already a small fraction of long-range couplings is sufficient to destroy coherent pattern formation. We argue that the small-world network topology destroys spatial order due to the lack of a precise internal spatial scale, which by regular connectivity is given by the coupling constant and the noise robust excursion time that is characteristic for the local dynamics. Additionally, the importance of spatially versus temporally ordered neural network functioning is discussed.

Characterization of pancreatic NMDA receptors as possible drug targets for diabetes treatment

Abstract: In the nervous system, NMDA receptors (NMDARs) participate in neurotransmission and modulate the viability of neurons. In contrast, little is known about the role of NMDARs in pancreatic islets and the insulin-secreting beta cells whose functional impairment contributes to diabetes mellitus. Here we found that inhibition of NMDARs in mouse and human islets enhanced their glucose-stimulated insulin secretion (GSIS) and survival of islet cells. Further, NMDAR inhibition prolonged the amount of time that glucose-stimulated beta cells spent in a depolarized state with high cytosolic Ca(2+) concentrations. We also noticed that, in vivo, the NMDAR antagonist dextromethorphan (DXM) enhanced glucose tolerance in mice, and that in vitro dextrorphan, the main metabolite of DXM, amplified the stimulatory effect of exendin-4 on GSIS. In a mouse model of type 2 diabetes mellitus (T2DM), long-term treatment with DXM improved islet insulin content, islet cell mass and blood glucose control. Further, in a small clinical trial we found that individuals with T2DM treated with DXM showed enhanced serum insulin concentrations and glucose tolerance. Our data highlight the possibility that antagonists of NMDARs may provide a useful adjunct treatment for diabetes.