1. 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: 358
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2. Synchronous bursts on scale-free neuronal networks with attractive and repulsive couplingQingyun Wang, Guanrong Chen, Matjaž Perc, 2011, original scientific article Abstract: This paper investigates the dependence of synchronization transitions of bursting oscillations on the information transmission delay over scale-free neuronal networks with attractive and repulsive coupling. It is shown that for both types of coupling, the delay always plays a subtle role in either promoting or impairing synchronization. In particular, depending on the inherent oscillation period of individual neurons, regions of irregular and regular propagating excitatory fronts appear intermittently as the delay increases. These delay-induced synchronization transitions are manifested as well-expressed minima in the measure for spatiotemporal synchrony. For attractive coupling, the minima appear at every integer multiple of the average oscillation period, while for the repulsive coupling, they appear at every odd multiple of the half of the average oscillation period. The obtained results are robust to the variations of the dynamics of individual neurons, the system size, and the neuronal firing type. Hence, they can be used to characterize attractively or repulsively coupled scale-free neuronal networks with delays.
Keywords: synchronization, neuronal networks, noise, stochastic processes, scale-free networks, information transmission delay
Published in DKUM: 19.06.2017; Views: 1218; Downloads: 388
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3. Modeling the seasonal adaptation of circadian clocks by changes in the network structure of the suprachiasmatic nucleusChristian Bodenstein, Marko Gosak, Stefan Schuster, Marko Marhl, Matjaž Perc, 2012, original scientific article Abstract: The dynamics of circadian rhythms needs to be adapted to day length changes between summer and winter. It has been observed experimentally, however, that the dynamics of individual neurons of the suprachiasmatic nucleus (SCN) does not change as the seasons change. Rather, the seasonal adaptation of the circadian clock is hypothesized to be a consequence of changes in the intercellular dynamics, which leads to a phase distribution of electrical activity of SCN neurons that is narrower in winter and broader during summer. Yet to understand this complex intercellular dynamics, a more thorough understanding of the impact of the network structure formed by the SCN neurons is needed. To that effect, we propose a mathematical model for the dynamics of the SCN neuronal architecture in which the structure of the network plays a pivotal role. Using our model we show that the fraction of long-range cell-to-cell connections and the seasonal changes in the daily rhythms may be tightly related. In particular, simulations of the proposed mathematical model indicate that the fraction of long-range connections between the cells adjusts the phase distribution and consequently the length of the behavioral activity as follows: dense long-range connections during winter lead to a narrow activity phase, while rare long-range connections during summer lead to a broad activity phase. Our model is also able to account for the experimental observations indicating a larger light-induced phase-shift of the circadian clock during winter, which we show to be a consequence of higher synchronization between neurons. Our model thus provides evidence that the variations in the seasonal dynamics of circadian clocks can in part also be understood and regulated by the plasticity of the SCN network structure.
Keywords: circadian rhythms, neuronal networks, small world, structures
Published in DKUM: 16.06.2017; Views: 1312; Downloads: 358
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