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

Özer, Mahmut

Article | 2004 | NeuroReport15 ( 9 ) , pp.1451 - 1455

We previously formulated dynamics of ion channel gates by the path probability method. In this study, we apply that theoretical approach to derive the activation rate kinetics of T-type calcium channel in thalamic relay neurons. We derive explicit expressions of the forward and backward rate constants and show that the proposed rate constants accurately capture form of the empirical time constant, and that they also provide its saturation to a constant value at depolarized membrane potentials. We also compare our derivations with linear and nonlinear thermodynamic models of rate kinetics obtained from the same calcium channel, and s . . .how that it is possible to capture saturation of the time constant for the depolarized membrane potentials by the only proposed rate constants. © 2004 Lippincott Williams & Wilkins Daha fazlası Daha az

Özer, Mahmut | Graham, Lyle J. | Erkaymaz, Okan | Uzuntarla, Muhammet

Article | 2007 | NeuroReport18 ( 13 ) , pp.1371 - 1374

Cortical neurons in-vivo operate in a continuum of overall conductance states, depending on the average level of background synaptic input throughout the dendritic tree. We compare how variability, or fluctuations, in this input affects the statistics of the resulting 'spontaneous' or 'background' firing activity, between two extremes of the mean input corresponding to a low-conductance (LC) and a high-conductance (HC) state. In the HC state, we show that both firing rate and regularity increase with increasing variability. In the LC state, firing rate also increases with input variability, but in contrast to the HC state, firing re . . .gularity first decreases and then increases with an increase in the variability. At high levels of input variability, firing regularity in both states converge to similar values. © 2007 Lippincott Williams & Wilkins, Inc Daha fazlası Daha az

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

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

Özer, Mahmut | Provaznik, Ivo

Article | 2005 | JOURNAL OF THEORETICAL BIOLOGY233 ( 2 ) , pp.237 - 243

The precise form of the rate constant functions of ion channels is very crucial for reproducing the electrophysiological behavior. Therefore, how well they account for experimental data plays an important role in the behavior of the model. In this study, we derive kinetic coefficients of activation and inactivation gates in ion channels by Onsager reciprocity theorem for an ensemble of gating particles, and propose that the obtained kinetic coefficients can be used as a comparative tool for the empirical validity of fitted rate constant functions to experimental data. We also illustrate its applicability based on the activation and . . .inactivation kinetics of T-type calcium channel in thalamic relay neurons. We show that the shape of the steady-state curve by itself seems to be a poor indicator of the functional form of the rate functions, but the time constant curves reflect considerable variation depending on the particular form of the rate functions, and that the kinetic coefficients related to the time constants provide a powerful tool to determine the empirical validity of the fitted rate constants. (C) 2004 Elsevier Ltd. All rights reserved Daha fazlası Daha az

Onur, Tuğba Özge | Carlson, Johan E | Svanström, Erika | Hacıoğlu, Rıfat

Article | 2019 | Iranian Journal of Science and Technology - Transactions of Electrical Engineering43 ( 3 ) , pp.405 - 413

This paper demonstrates how flexural wave propagation in a thin plate can be modeled by estimating the combined effect of the excitation source signal and the impulse response of the ultrasonic sensor. The wave propagation in the plate is modeled using the wave equation for the flexural wave mode. A theoretical model for flexural wave propagation in thin plates has been derived, and it has been compared with measurements excited by tapping gently on the surface. The combined effects of the excitation source signal and the impulse response of the low-cost piezoelectric sensor are modeled using finite-impulse response and/or infinite- . . .impulse response filters. Thereafter, the performances of the selected filters are compared on estimating the wave propagation in a thin quartz glass plate. Results indicate that the most accurate estimation of wave propagation has been obtained using a linear phase filter which attributes all dispersions to the flexural wave. © 2018, Shiraz University Daha fazlası Daha az

Onur, Tuğba Özge | Hacıoğlu, Rıfat

Article | 2017 | Turkish Journal of Electrical Engineering and Computer Sciences25 ( 2 ) , pp.939 - 949

We investigated adaptive algorithms for a Hammerstein block structure in which a static nonlinear block and dynamic linear block are cascaded. The approach considered here is to use generalized orthonormal basis functions in a Hammerstein block structure by using xed pole lter banks. We applied the normalized least mean square approach to the developed adaptive algorithm in order to acquire Hammerstein block structure parameters. Performance comparison of the proposed approach was investigated considering convergence speed and parametric complexity for acoustic echo cancellation application. The results indicated that in the develop . . .ed algorithm along with appropriate selection of xed poles, the algorithm convergences faster and less parametric complexity is provided when compared to direct adaptive Hammerstein algorithms with IIR and FIR linear blocks. We investigated adaptive algorithms for a Hammerstein block structure in which a static nonlinear block and dynamic linear block are cascaded. The approach considered here is to use generalized orthonormal basis functions in a Hammerstein block structure by using xed pole lter banks. We applied the normalized least mean square approach to the developed adaptive algorithm in order to acquire Hammerstein block structure parameters. Performance comparison of the proposed approach was investigated considering convergence speed and parametric complexity for acoustic echo cancellation application. The results indicated that in the developed algorithm along with appropriate selection of xed poles, the algorithm convergences faster and less parametric complexity is provided when compared to direct adaptive Hammerstein algorithms with IIR and FIR linear blocks Daha fazlası Daha az

Altan, Aytaç | Hacıoğlu, Rıfat

Article | 2018 | JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI21 ( 3 ) , pp.559 - 564

The 3D printers widely used in the world are produced in different mechanical and electronic designs. The 3D printers which have various mechanical structures such as cartesian, delta and core (xy, xz) already are used open source code software such as Sprinter, Marlin, Cura 3D and Teacup. The control of the 3D printers is usually done by the classical Propotional-Integral-Derivative (PID) control algorithm. In this study, we have developed for the designed 3D printer a new software by using adaptive PID control algorithm instead of classical PID. Five step motors of the designed 3D printer are controlled by the adaptive PID. In add . . .ition, there are both heating and cooling processes in the extruder system and these processes are controlled by the adaptive PID. The mechanical design uses a belt and pulley drive system which is suitable for accelerated movements. In the system software, 3D Printing Software Pipeline (input model, orientation and positioning, support structures, slicing, path planning, machine instructions) is applied. The control algorithms for extruder and step motors are prepared as separate function files in software implemented in C. It has been observed that the designed software is particularly successful in eliminating errors on the surface of the products Daha fazlası Daha az

Erkaymaz, Okan | Özer, Mahmut | Perc, Matjaž

Article | 2017 | Applied Mathematics and Computation311 , pp.22 - 28

We investigate the performance of two different small-world feedforward neural networks for the diagnosis of diabetes. We use the Pima Indians Diabetic Dataset as input. We have previously shown than the Watts–Strogatz small-world feedforward neural network delivers a better classification performance than conventional feedforward neural networks. Here, we compare this performance further with the one delivered by the Newman–Watts small-world feedforward neural network, and we show that the latter is better still. Moreover, we show that Newman–Watts small-world feedforward neural networks yield the highest output correlation as well . . . as the best output error parameters. © 2017 Elsevier Inc Daha fazlası Daha az

Erkaymaz, Hande | Özer, Mahmut | Orak, İlhami Muharrem

Article | 2015 | Chaos, Solitons and Fractals77 , pp.225 - 229

The electrooculogram signals are very important at extracting information about detection of directional eye movements. Therefore, in this study, we propose a new intelligent detection model involving an artificial neural network for the eye movements based on the electrooculogram signals. In addition to conventional eye movements, our model also involves the detection of tic and blinking of an eye. We extract only two features from the electrooculogram signals, and use them as inputs for a feed-forwarded artificial neural network. We develop a new approach to compute these two features, which we call it as a movement range. The res . . .ults suggest that the proposed model have a potential to become a new tool to determine the directional eye movements accurately. © 2015 Elsevier Ltd. All rights reserved Daha fazlası Daha az

Erkaymaz, Okan | Özer, Mahmut

Article | 2016 | Chaos, Solitons and Fractals83 , pp.178 - 185

Artificial intelligent systems have been widely used for diagnosis of diseases. Due to their importance, new approaches are attempted consistently to increase the performance of these systems. In this study, we introduce a new approach for diagnosis of diabetes based on the Small-World Feed Forward Artificial Neural Network (SW- FFANN). We construct the small-world network by following the Watts-Strogatz approach, and use this architecture for classifying the diabetes, and compare its performance with that of the regular or the conventional FFANN. We show that the classification performance of the SW-FFANN is better than that of the . . . conventional FFANN. The SW-FFANN approach also results in both the highest output correlation and the best output error parameters. We also perform the accuracy analysis and show that SW-FFANN approach exhibits the highest classifier performance. © 2015 Elsevier Ltd. All rights reserved Daha fazlası Daha az