1. Determinants of collective failure in excitable networksUroš Barać, Matjaž Perc, Marko Gosak, 2023, original scientific article Abstract: We study collective failures in biologically realistic networks that consist of coupled excitable units. The networks have broad-scale degree distribution, high modularity, and small-world properties, while the excitable dynamics is determined by the paradigmatic FitzHugh–Nagumo model. We consider different coupling strengths, bifurcation distances, and various aging scenarios as potential culprits of collective failure. We find that for intermediate coupling strengths, the network remains globally active the longest if the high-degree nodes are first targets for inactivation. This agrees well with previously published results, which showed that oscillatory networks can be highly fragile to the targeted inactivation of low-degree nodes, especially under weak coupling. However, we also show that the most efficient strategy to enact collective failure does not only non-monotonically depend on the coupling strength, but it also depends on the distance from the bifurcation point to the oscillatory behavior of individual excitable units. Altogether, we provide a comprehensive account of determinants of collective failure in excitable networks, and we hope this will prove useful for better understanding breakdowns in systems that are subject to such dynamics.
Keywords: collective behavior, excitable media, complex network, neuronal dynamics
Published in DKUM: 10.06.2024; Views: 163; Downloads: 14
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2. Interlayer and intralayer synchronization in multiplex fractional-order neuronal networksBo Yan, Fatemeh Parastesh, Shaobo He, Karthikeyan Rajagopal, Sajad Jafari, Matjaž Perc, 2022, original scientific article Abstract: Fractional-order models describing neuronal dynamics often exhibit better compatibility with diverse neuronal firing patterns that can be observed experimentally. Due to the overarching significance of synchronization in neuronal dynamics, we here study synchronization in multiplex neuronal networks that are composed of fractional-order Hindmarsh-Rose neurons. We compute the average synchronization error numerically for different derivative orders in dependence on the strength of the links within and between network layers. We find that, in general, fractional-order models synchronize better than integer-order models. In particular, we show that the required interlayer and intralayer coupling strengths for interlayer or intralayer synchronization can be weaker if we reduce the derivative order of the model describing the neuronal dynamics. Furthermore, the dependence of the interlayer or intralayer synchronization on the intralayer or interlayer coupling strength vanishes with decreasing derivative order. To support these results analytically, we use the master stability function approach for the considered multiplex fractional-order neuronal networks, by means of which we obtain sufficient conditions for the interlayer and intralayer synchronizations that are in agreement with numerical results.
Keywords: synchronization, neuronal network, multilayer network, neuronal dynamics
Published in DKUM: 28.05.2024; Views: 230; Downloads: 0 |
3. Fast random rewiring and strong connectivity impair subthreshold signal detection in excitable networksVladislav Volman, Matjaž Perc, 2010, original scientific article Abstract: We study dynamical responses in locally paced networks consisting of diffusively coupled excitable units with dynamically adjusted connectivity. It is shown that for weak subthreshold pacing, excessive or strong connectivity impairs the reliable response of a network to the stimulus. Fast random dynamic rewiring of the network also acts detrimentally on signal detection by enforcing a faster relaxation upon the paced unit. Our results indicate that efficient signal processing on excitable complex networks requires tight correspondence between the dynamics of connectivity and the dynamical processes taking place on the network. This, in turn, suggests the existence of 'function-follows-form' principles for systems described within this framework.
Keywords: neuronal dynamics, complex networks, coevolution, cognition
Published in DKUM: 03.07.2017; Views: 1321; Downloads: 351
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4. Regulation of irregular neuronal firing by autaptic transmissionDaqing Guo, Shengdun Wu, Mingming Chen, Matjaž Perc, Yangsong Zhang, Jingling Ma, Yan Cui, Peng Xu, Yang Xia, Dezhong Yao, 2016, original scientific article Abstract: The importance of self-feedback autaptic transmission in modulating spike-time irregularity is still poorly understood. By using a biophysical model that incorporates autaptic coupling, we here show that self-innervation of neurons participates in the modulation of irregular neuronal firing, primarily by regulating the occurrence frequency of burst firing. In particular, we find that both excitatory and electrical autapses increase the occurrence of burst firing, thus reducing neuronal firing regularity. In contrast, inhibitory autapses suppress burst firing and therefore tend to improve the regularity of neuronal firing. Importantly, we show that these findings are independent of the firing properties of individual neurons, and as such can be observed for neurons operating in different modes. Our results provide an insightful mechanistic understanding of how different types of autapses shape irregular firing at the single-neuron level, and they highlight the functional importance of autaptic self-innervation in taming and modulating neurodynamics.
Keywords: neuronal dynamics, autapse, regulation, excitation
Published in DKUM: 23.06.2017; Views: 1306; Downloads: 413
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5. Disinhibition-induced transitions between absence and tonic-clonic epileptic seizuresDenggui Fan, Qingyun Wang, Matjaž Perc, 2015, original scientific article Abstract: Electrophysiological experiments have long revealed the existence of two-way transitions between absence and tonic-clonic epileptic seizures in the cerebral cortex. Based on a modified spatially-extended Taylor & Baier neural field model, we here propose a computational framework to mathematically describe the transition dynamics between these epileptic seizures. We first demonstrate the existence of various transition types that are induced by disinhibitory functions between two inhibitory variables in an isolated Taylor & Baier model. Moreover, we show that these disinhibition-induced transitions can lead to stable tonic-clonic oscillations as well as periodic spike with slow-wave discharges, which are the hallmark of absence seizures. We also observe fascinating dynamical states, such as periodic 2-spike with slow-wave discharges, tonic death, bursting oscillations, as well as saturated firing. Most importantly, we identify paths that represent physiologically plausible transitions between absence and tonic-clonic seizures in the modified spatially-extended Taylor & Baier model.
Keywords: epilepsy, neuronal dynamics, synchronization, biophysics
Published in DKUM: 23.06.2017; Views: 1181; Downloads: 366
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6. Autapse-induced multiple coherence resonance in single neurons and neuronal networksErgin Yilmaz, Mahmut Özer, Veli Baysal, Matjaž Perc, 2016, original scientific article Abstract: We study the effects of electrical and chemical autapse on the temporal coherence or firing regularity of single stochastic Hodgkin-Huxley neurons and scale-free neuronal networks. Also, we study the effects of chemical autapse on the occurrence of spatial synchronization in scale-free neuronal networks. Irrespective of the type of autapse, we observe autaptic time delay induced multiple coherence resonance for appropriately tuned autaptic conductance levels in single neurons. More precisely, we show that in the presence of an electrical autapse, there is an optimal intensity of channel noise inducing the multiple coherence resonance, whereas in the presence of chemical autapse the occurrence of multiple coherence resonance is less sensitive to the channel noise intensity. At the network level, we find autaptic time delay induced multiple coherence resonance and synchronization transitions, occurring at approximately the same delay lengths. We show that these two phenomena can arise only at a specific range of the coupling strength, and that they can be observed independently of the average degree of the network.
Keywords: neuronal dynamics, autapse, coherence resonance, scale-free network
Published in DKUM: 23.06.2017; Views: 1163; Downloads: 438
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7. Spatial coherence resonance in excitable biochemical media induced by internal noiseMarko Gosak, Marko Marhl, Matjaž Perc, 2007, original scientific article Abstract: We show that in a spatially extended excitable medium, presently modelled with diffusively coupled FitzHugh-Nagumo neurons, internal stochasticity is able to extract a characteristic spatial frequency of waves on the spatial grid. Internal noise is introduced via a stochastic simulation method and is the only agent acting on the system. Remarkably, the spatial periodicity is best pronounced at an intermediate level of internal stochasticity. Thus, the reported phenomenon is an observation of internal noise spatial coherence resonance in excitable biochemical media.
Keywords: noise, spatiotemporal noise, intensity, spatial resonance, spatial coherence resonance, excitable media, excitable biochemical media, neuronal dynamics, internal noise
Published in DKUM: 07.06.2012; Views: 1735; Downloads: 83
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