Iskanje po katalogu digitalne knjižnice

Opis: When individual oscillators age and become inactive, the collective dynamics of coupled oscillators is often affected as well. Depending on the fraction of inactive oscillators or cascading failures that percolate from crucial information exchange points, the critical shift toward macroscopic inactivity in coupled oscillator networks is known as the aging transition. Here, we study this phenomenon in two overlayed square lattices that together constitute a multilayer network, whereby one layer is populated with slow Poincaré oscillators and the other with fast Rulkov neurons. Moreover, in this multimodal setup, the excitability of fast oscillators is influenced by the phase of slow oscillators that are gradually inactivated toward the aging transition in the fast layer. Through extensive numerical simulations, we find that the progressive inactivation of oscillators in the slow layer nontrivially affects the collective oscillatory activity and the aging transitions in the fast layer. Most counterintuitively, we show that it is possible for the intensity of oscillatory activity in the fast layer to progressively increase to up to 100%, even when up to 60% of units in the slow oscillatory layer are inactivated. We explain our results with a numerical analysis of collective behavior in individual layers, and we discuss their implications for biological systems.
Ključne besede: collective dynamics, coupled oscillators, dynamics of networks, network resilience, robustness, synchronization transition
Objavljeno v DKUM: 28.02.2025; Ogledov: 0; Prenosov: 425
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Opis: Background: The crucial steps in beta cell stimulus-secretion coupling upon stimulation with glucose are oscillatory changes in metabolism, membrane potential, intracellular calcium concentration, and exocytosis. The changes in membrane potential consist of bursts of spikes, with silent phases between them being dominated by membrane repolarization and absence of spikes. Assessing intra- and intercellular coupling at the multicellular level is possible with ever-increasing detail, but our current ability to simultaneously resolve spikes from many beta cells remains limited to double-impalement electrophysiological recordings. Methods: Since multicellular calcium imaging of spikes would enable a better understanding of coupling between changes in membrane potential and calcium concentration in beta cell collectives, we set out to design an appropriate methodological approach. Results: Combining the acute tissue slice method with ultrafast calcium imaging, we were able to resolve and quantify individual spikes within bursts at a temporal resolution of >150 Hz over prolonged periods, as well as describe their glucose-dependent properties. In addition, by simultaneous patch-clamp recordings we were able to show that calcium spikes closely follow membrane potential changes. Both bursts and spikes coordinate across islets in the form of intercellular waves, with bursts typically displaying global and spikes more local patterns. Conclusions: This method and the associated findings provide additional insight into the complex signaling within beta cell networks. Once extended to tissue from diabetic animals and human donors, this approach could help us better understand the mechanistic basis of diabetes and find new molecular targets.
Ključne besede: beta cell, calcium imaging, calcium oscillations, calcium spikes, physiology
Objavljeno v DKUM: 24.01.2025; Ogledov: 0; Prenosov: 7
Celotno besedilo (9,70 MB)
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Opis: The firing patterns of neuronal populations often exhibit emergent collective oscillations, which can display substantial regularity even though the dynamics of individual elements is very stochastic. One of the many phenomena that is often studied in this context is coherence resonance, where additional noise leads to improved regularity of spiking activity in neurons. In this work, we investigate how the coherence resonance phenomenon manifests itself in populations of excitatory and inhibitory neurons. In our simulations, we use the coupled FitzHugh-Nagumo oscillators in the excitable regime and in the presence of neuronal noise. Formally, our model is based on the concept of a two-layered network, where one layer contains inhibitory neurons, the other excitatory neurons, and the interlayer connections represent heterotypic interactions. The neuronal activity is simulated in realistic coupling schemes in which neurons within each layer are connected with undirected connections, whereas neurons of different types are connected with directed interlayer connections. In this setting, we investigate how different neurophysiological determinants affect the coherence resonance. Specifically, we focus on the proportion of inhibitory neurons, the proportion of excitatory interlayer axons, and the architecture of interlayer connections between inhibitory and excitatory neurons. Our results reveal that the regularity of simulated neural activity can be increased by a stronger damping of the excitatory layer. This can be accomplished with a higher proportion of inhibitory neurons, a higher fraction of inhibitory interlayer axons, a stronger coupling between inhibitory axons, or by a heterogeneous configuration of interlayer connections. Our approach of modeling multilayered neuronal networks in combination with stochastic dynamics offers a novel perspective on how the neural architecture can affect neural information processing and provide possible applications in designing networks of artificial neural circuits to optimize their function via noise-induced phenomena.
Ključne besede: neuronal dynamics, coherence resonance, excitatory neurons, inhibitory neurons, neural network, multilayer network, interlayer connectivity
Objavljeno v DKUM: 20.12.2024; Ogledov: 0; Prenosov: 4
Celotno besedilo (6,72 MB)
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Opis: Within the islets of Langerhans, beta cells orchestrate synchronized insulin secretion, a pivotal aspect of metabolic homeostasis. Despite the inherent heterogeneity and multimodal activity of individual cells, intercellular coupling acts as a homogenizing force, enabling coordinated responses through the propagation of intercellular waves. Disruptions in this coordination are implicated in irregular insulin secretion, a hallmark of diabetes. Recently, innovative approaches, such as integrating multicellular calcium imaging with network analysis, have emerged for a quantitative assessment of the cellular activity in islets. However, different groups use distinct experimental preparations, microscopic techniques, apply different methods to process the measured signals and use various methods to derive functional connectivity patterns. This makes comparisons between findings and their integration into a bigger picture difficult and has led to disputes in functional connectivity interpretations. To address these issues, we present here a systematic analysis of how different approaches influence the network representation of islet activity. Our findings show that the choice of methods used to construct networks is not crucial, although care is needed when combining data from different islets. Conversely, the conclusions drawn from network analysis can be heavily affected by the pre-processing of the time series, the type of the oscillatory component in the signals, and by the experimental preparation. Our tutorial-like investigation aims to resolve interpretational issues, reconcile conflicting views, advance functional implications, and encourage researchers to adopt connectivity analysis. As we conclude, we outline challenges for future research, emphasizing the broader applicability of our conclusions to other tissues exhibiting complex multicellular dynamics.
Ključne besede: islets of Langerhans, beta cells, calcium signaling, intercellular communication, functional networks, myosin model
Objavljeno v DKUM: 09.12.2024; Ogledov: 0; Prenosov: 4
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Opis: We propose and study an epidemiological model on a social network that takes into account heterogeneity of the population and different vaccination strategies. In particular, we study how the COVID-19 epidemics evolves and how it is contained by different vaccination scenarios by taking into account data showing that older people, as well as individuals with comorbidities and poor metabolic health, and people coming from economically depressed areas with lower quality of life in general, are more likely to develop severe COVID-19 symptoms, and quicker loss of immunity and are therefore more prone to reinfection. Our results reveal that the structure and the spatial arrangement of subpopulations are important epidemiological determinants. In a healthier society the disease spreads more rapidly but the consequences are less disastrous as in a society with more prevalent chronic comorbidities. If individuals with poor health are segregated within one community, the epidemic outcome is less favorable. Moreover, we show that, contrary to currently widely adopted vaccination policies, prioritizing elderly and other higher-risk groups is beneficial only if the supply of vaccine is high. If, however, the vaccination availability is limited, and if the demographic distribution across the social network is homogeneous, better epidemic outcomes are achieved if healthy people are vaccinated first. Only when higher-risk groups are segregated, like in elderly homes, their prioritization will lead to lower COVID-19 related deaths. Accordingly, young and healthy individuals should view vaccine uptake as not only protecting them, but perhaps even more so protecting the more vulnerable socio-demographic groups.
Ključne besede: epidemic model, COVID-19, vaccination strategy, vaccination strategy, population heterogeneity, socio-demographic structure, metabolic disease, social network
Objavljeno v DKUM: 14.11.2024; Ogledov: 0; Prenosov: 12
Celotno besedilo (7,09 MB)
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