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Autapse-induced multiple coherence resonance in single neurons and neuronal networks

Yılmaz, Ergin | Özer, Mahmut | Baysal, Veli | Perc, Matjaž

Article | 2016 | Scientific Reports6

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 resonanc . . .e, 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. © The Author(s) 2016 Daha fazlası Daha az

Enhancement of pacemaker induced stochastic resonance by an autapse in a scale-free neuronal network

Yılmaz, Ergin | Baysal, Veli | Perc, Matjaž | Özer, Mahmut

Article | 2016 | Science China Technological Sciences59 ( 3 ) , pp.364 - 370

An autapse is an unusual synapse that occurs between the axon and the soma of the same neuron. Mathematically, it can be described as a self-delayed feedback loop that is defined by a specific time-delay and the so-called autaptic coupling strength. Recently, the role and function of autapses within the nervous system has been studied extensively. Here, we extend the scope of theoretical research by investigating the effects of an autapse on the transmission of a weak localized pacemaker activity in a scale-free neuronal network. Our results reveal that by mediating the spiking activity of the pacemaker neuron, an autapse increases . . .the propagation of its rhythm across the whole network, if only the autaptic time delay and the autaptic coupling strength are properly adjusted. We show that the autapse-induced enhancement of the transmission of pacemaker activity occurs only when the autaptic time delay is close to an integer multiple of the intrinsic oscillation time of the neurons that form the network. In particular, we demonstrate the emergence of multiple resonances involving the weak signal, the intrinsic oscillations, and the time scale that is dictated by the autapse. Interestingly, we also show that the enhancement of the pacemaker rhythm across the network is the strongest if the degree of the pacemaker neuron is lowest. This is because the dissipation of the localized rhythm is contained to the few directly linked neurons, and only afterwards, through the secondary neurons, it propagates further. If the pacemaker neuron has a high degree, then its rhythm is simply too weak to excite all the neighboring neurons, and propagation therefore fails. © 2016, Science China Press and Springer-Verlag Berlin Heidelberg Daha fazlası Daha az

Enhancement of temporal coherence via time-periodic coupling strength in a scale-free network of stochastic Hodgkin-Huxley neurons

Yılmaz, Ergin | Baysal, Veli | Özer, Mahmut

Article | 2015 | Physics Letters, Section A: General, Atomic and Solid State Physics379 ( 26-27 ) , pp.1594 - 1599

We investigate the effects of time-periodic coupling strength on the temporal coherence or firing regularity of a scale-free network consisting of stochastic Hodgkin-Huxley (H-H) neurons. The temporal coherence exhibits a resonance-like behavior depending on the cell size or the channel noise intensity. The best temporal coherence requires an optimal channel noise intensity, and this coherence can be significantly increased by time-periodic coupling strength when its frequency matches the integer multiples of the intrinsic subthreshold oscillation frequency of H-H neuron. Particularly, we find the multiple-coherence resonance depend . . .ing on frequency of time-periodic coupling strength at the optimal noise intensity. We also obtain a resonance-like dependence of temporal coherence on the amplitude of time-periodic coupling strength. Additionally, we investigate the effects of average degree on the temporal coherence and find that the temporal coherence exhibits a resonance-like behavior with respect to the network average degree, indicating that the best regularity requires an optimal average degree. © 2015 Elsevier B.V. All rights reserved Daha fazlası Daha az

Vibrational resonance in a heterogeneous scale free network of neurons

Uzuntarla, Muhammet | Yılmaz, Ergin | Wagemakers, Alexandre | Özer, Mahmut

Article | 2015 | Communications in Nonlinear Science and Numerical Simulation22 ( 01.Mar ) , pp.367 - 374

Vibrational resonance (VR) is a phenomenon whereby the response of some dynamical systems to a weak low-frequency signal can be maximized with the assistance of an optimal intensity of another high-frequency signal. In this paper, we study the VR in a heterogeneous neural system having a complex network topology. We consider a scale-free network of neurons where the heterogeneity is in the intrinsic excitability of the individual neurons. It is shown that emergence of VR in heterogeneous neuron population requires less energy than a homogeneous population. We also find that electrical coupling strength among neurons plays a key role . . . in determining the weak signal processing capacity of the heterogeneous population. Lastly, we investigate the influence of interneuronal link density on the VR and demonstrate that the energy needed to obtain the resonance grows with the increase in average degree. © 2014 Elsevier B.V Daha fazlası Daha az

Delayed feedback and detection of weak periodic signals in a stochastic Hodgkin-Huxley neuron

Yılmaz, Ergin | Özer, Mahmut

Article | 2015 | Physica A: Statistical Mechanics and its Applications421 , pp.455 - 462

We study the effect of the delayed feedback loop on the weak periodic signal detection performance of a stochastic Hodgkin-Huxley neuron. We consider an electrical autapse characterized by its coupling strength and delay time. The stochastic Hodgkin-Huxley neuron exhibits subthreshold oscillations, and thus has an intrinsic time scale with the subthreshold oscillations. Therefore, we investigate the interplay of the subthreshold oscillations, coupling strength and delay time on the weak periodic signal detection. Results indicate that the delayed feedback either enhances or suppresses the weak signal detection depending on its param . . .eters, when compared to that without the feedback. The delayed feedback augments the weak periodic signal detection for the optimal values of the intrinsic noise and the coupling strength when the delay time is close to the integer multiples of the period of the intrinsic oscillations, due to the multiple resonance among the weak signal, the intrinsic oscillations, and the delayed feedback. We analyze the interspike interval histograms and show that the delayed feedback enhances or suppresses the weak periodic signal detection by increasing or decreasing the phase locking (synchronization) between the spiking and the weak periodic signal. We also show that an optimal phase locking is obtained when the delay time is close to the period of the intrinsic oscillations, leading a single dominant time scale in the spike trains. © 2014 Elsevier B.V. All rights reserved Daha fazlası Daha az

Collective firing regularity of a scale-free Hodgkin-Huxley neuronal network in response to a subthreshold signal

Yılmaz, Ergin | Özer, Mahmut

Article | 2013 | Physics Letters, Section A: General, Atomic and Solid State Physics377 ( 18 ) , pp.1301 - 1307

We consider a scale-free network of stochastic HH neurons driven by a subthreshold periodic stimulus and investigate how the collective spiking regularity or the collective temporal coherence changes with the stimulus frequency, the intrinsic noise (or the cell size), the network average degree and the coupling strength. We show that the best temporal coherence is obtained for a certain level of the intrinsic noise when the frequencies of the external stimulus and the subthreshold oscillations of the network elements match. We also find that the collective regularity exhibits a resonance-like behavior depending on both the coupling . . .strength and the network average degree at the optimal values of the stimulus frequency and the cell size, indicating that the best temporal coherence also requires an optimal coupling strength and an optimal average degree of the connectivity. © 2013 Elsevier B.V Daha fazlası Daha az

Dynamical structure underlying inverse stochastic resonance and its implications

Uzuntarla, Muhammet | Cressman John R. | Özer, Mahmut | Barreto, Erenest

Article | 2013 | Physical Review E - Statistical, Nonlinear, and Soft Matter Physics88 ( 4 ) , pp.1301 - 1307

We investigate inverse stochastic resonance (ISR), a recently reported phenomenon in which the spiking activity of a Hodgkin-Huxley model neuron subject to external noise exhibits a pronounced minimum as the noise intensity increases. We clarify the mechanism that underlies ISR and show that its most surprising features are a consequence of the dynamical structure of the model. Furthermore, we show that the ISR effect depends strongly on the procedures used to measure it. Our results are important for the experimentalist who seeks to observe the ISR phenomenon. © 2013 American Physical Society.

Synchronization-induced spike termination in networks of bistable neurons

Uzuntarla, Muhammet | Torres, Joaquin J. | Çalım, Ali | Barreto, Ernest

Article | 2019 | Neural Networks110 , pp.131 - 140

We observe and study a self-organized phenomenon whereby the activity in a network of spiking neurons spontaneously terminates. We consider different types of populations, consisting of bistable model neurons connected electrically by gap junctions, or by either excitatory or inhibitory synapses, in a scale-free connection topology. We find that strongly synchronized population spiking events lead to complete cessation of activity in excitatory networks, but not in gap junction or inhibitory networks. We identify the underlying mechanism responsible for this phenomenon by examining the particular shape of the excitatory postsynaptic . . . currents that arise in the neurons. We also examine the effects of the synaptic time constant, coupling strength, and channel noise on the occurrence of the phenomenon. © 2018 Elsevier Lt Daha fazlası Daha az

Advances in renewable energy and energy efficiency technologies Preface

Çavdar, İsmail Hakkı | Suljanovic, Nermin | Uzuntarla, Muhammet


WOS: 000365508200001

Effects of astrocyte on weak signal detection performance of Hodgkin–Huxley neuron

Erkan, Yasemin | Saraç, Zehra | Yılmaz, Ergin

Article | 2019 | Nonlinear Dynamics95 ( 4 ) , pp.3411 - 3421

By virtue of recent developments in brain measurement technology, it is now recognized that information processing in brain includes not only neurons but also astrocytes. For this reason, to illustrate the effects of astrocyte on information processing in neuronal systems, we research the weak signal detection performance of the Hodgkin–Huxley neuron under the effect of astrocyte. It is found that the weak signal detection performance of the neuron exhibits the stochastic resonance phenomenon depending on noise intensity, where the presence of astrocyte with an optimal coupling strength significantly increases the detection performa . . .nce of the neuron when compared the one without astrocyte. The obtained results also reveal that there is an optimal weak signal frequency ensuring the best detection performance. Besides, we show that the colored noise exhibits a better performance than white Gaussian noise on improving the weak signal detection capacity of the neuron; moreover, the weak signal detection performance of the neuron demonstrates a resonance-like dependence on the correlation time of the noise. Finally, we investigate the effects of calcium channel noise. Although the calcium channel noise generally reduces the weak signal detection performance of the neuron, the optimal coupling strength warranting the best detection performance critically depends on its intensity. © 2019, Springer Nature B.V Daha fazlası Daha az

Chaotic resonance in Hodgkin-Huxley neuron

Baysal, Veli | Saraç, Zehra | Yılmaz, Ergin

Article | 2019 | NONLINEAR DYNAMICS97 ( 2 ) , pp.1275 - 1285

Chaotic Resonance (CR), whereby the response of a nonlinear system to a weak signal can be enhanced by the assistance of chaotic activities that can be intrinsic or extrinsic, has recently been studied widely. In this paper, the effects of extrinsic chaotic signal on the weak signal detection performance of the Hodgkin-Huxley neuron are examined via numerical simulation. The chaotic signal has been derived from Lorenz system and is injected to neuron as a current. Obtained results have revealed that the H-H neuron exhibits CR phenomenon depending on the chaotic current intensity. Also, we have found an optimal chaotic current intens . . .ity ensuring the best detection of the weak signal in H-H neuron via CR. In addition, we have calculated the maximal Lyapunov exponent to determine whether the H-H neuron is in chaotic regime. After determining the state of the neuron, we have shown that the H-H neuron can be able to detect the weak signal even if it is in the chaotic regime. Finally, we have investigated the effects of chaotic activity on the collective behavior of H-H neurons in small-world networks and have concluded that CR effect is a robust phenomenon which can be observed both in single neurons and neuronal networks Daha fazlası Daha az

Chimera states in networks of type-I Morris-Lecar neurons

Çalım, Ali | Hövel, Philipp | Özer, Mahmut | Uzuntarla, Muhammet

Article | 2018 | Physical Review E98 ( 6 ) , pp.1275 - 1285

Chimeras are complex spatiotemporal patterns that emerge as coexistence of both coherent and incoherent groups of coupled dynamical systems. Here, we investigate the emergence of chimera states in nonlocal networks of type-I Morris-Lecar neurons coupled via chemical synapses. This constitutes a more realistic neuronal modeling framework than previous studies of chimera states, since the Morris-Lecar model provides biophysically more relevant control parameters to describe the activity in actual neural systems. We explore systematically the transitions of dynamic behavior and find that different types of synchrony appear depending on . . . the excitability level and nonlocal network features. Furthermore, we map the transitions between incoherent states, traveling waves, chimeras, coherent states, and global amplitude death in the parameter space of interest. This work contributes to a better understanding of biological conditions giving rise to the emergence of chimera states in neural medium. © 2018 American Physical Society Daha fazlası Daha az

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