Yılmaz, Ergin

Article | 2014 | Chaos, Solitons and Fractals66 , pp.1 - 8

We study the phenomenon of noise-delayed decay in a scale-free neural network consisting of excitable FitzHugh-Nagumo neurons. In contrast to earlier works, where only electrical synapses are considered among neurons, we primarily examine the effects of hybrid synapses on the noise-delayed decay in this study. We show that the electrical synaptic coupling is more impressive than the chemical coupling in determining the appearance time of the first-spike and more efficient on the mitigation of the delay time in the detection of a suprathreshold input signal. We obtain that hybrid networks including inhibitory chemical synapses have h . . .igher signal detection capabilities than those of including excitatory ones. We also find that average degree exhibits two different effects, which are strengthening and weakening the noise-delayed decay effect depending on the noise intensity. © 2014 Elsevier Ltd. All rights reserved Daha fazlası Daha az

Uzuntarla, Muhammet | Uzun, Rukiye | Yılmaz, Ergin | Özer, Mahmut | Perc, Matjaž

Article | 2013 | Chaos, Solitons and Fractals56 , pp.202 - 208

Noise-delayed decay occurs when the first-spike latency of a periodically forced neuron exhibits a maximum at particular noise intensity. Here we investigate this phenomenon at the network level, in particular by considering scale-free neuronal networks, and under the realistic assumption of noise being due to the stochastic nature of voltage-gated ion channels that are embedded in the neuronal membranes. We show that noise-delayed decay can be observed at the network level, but only if the synaptic coupling strength between the neurons is weak. In case of strong coupling or in a highly interconnected population the phenomenon vanis . . .hes, thus indicating that delays in signal detection can no longer be resonantly prolonged by noise. We also find that potassium channel noise plays a more dominant role in the occurrence of noise-delayed decay than sodium channel noise, and that poisoning the neuronal membranes may weakens or intensify the phenomenon depending on targeting. © 2013 Elsevier Ltd. All rights reserved Daha fazlası Daha az

Kaya, Ceren | Erkaymaz, Okan | Ayar, Orhan | Özer, Mahmut

Article | 2018 | Chaos, Solitons and Fractals114 , pp.164 - 174

In this study, we introduce two hybrid artificial neural network models with particle swarm optimization algorithm to diagnose diabetic retinopathy based on the Video-Oculography signals. The hybrid models use Discrete Wavelet Transform and Hilbert-Huang Transform separately to extract features from the signals. The classification performance of both models is analyzed comparatively. We show that the model based on Hilbert–Huang Transform exhibits better classification performance than the model based on the Discrete Wavelet Transform. © 2018 Elsevier Ltd