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Simulation of Parkinsonian Globus Pallidus Nuclei with various network motifs

Çalım, Ali | Özer, Mahmut | Uzuntarla, Muhammet

Proceedings | 2017 | 2017 Medical Technologies National Conference, TIPTEKNO 20172017-January , pp.1 - 4

Parkinson's disease is a neurodegenerative disorder that affect human life quite negatively with motor, cognitive and psychiatric way. Recent electrophysiological experiments have shown that Basal Ganglia, spaced in the midbrain, can lead to Parkinsonism. Beta frequency oscillations and irregular burstings are most important symptoms of Parkinson's disease. They appear in Globus Pallidus and Subtalamus nuclei during the disease. In this study, anatomical connection features that may give rise to emergence of burstings are investigated, simulating Globus Pallidus and Subtalamus nuclei numerically. © 2017 IEEE.

Effects of electrical autapse on first spike latency of Hodgkin-Huxley Neuron

Baysal, Veli | Yılmaz, Ergin | Özer, Mahmut

Proceedings | 2017 | 2017 Medical Technologies National Conference, TIPTEKNO 20172017-January , pp.1 - 4

In this paper, the effects of autapse on the first spike latency of the stochastic H-H neuron are examined. In the study, it is considered that H-H neuron has an electrical autapse and by applying a suprathreshold periodic signal to neuron the first spike times has been observed. Obtained results show that the first spike latency of H-H neuron increases prominently in a certain autaptic time delay with the increasing of autaptic conductance. Also, the first spike latency decreases with the increasing of autaptic conductance in a different autaptic time delay interval. In the context of these results, we come to conclusion that the a . . .utapse have played important roles on the control of first spike latency of stochastic H-H neurons. © 2017 IEEE Daha fazlası Daha az

Effects of short term synaptic depression on vibrational resonance in neuronal networks

Çalım, Ali | Özer, Mahmut | Uzuntarla, Muhammet

Proceedings | 2017 | 2017 Medical Technologies National Conference, TIPTEKNO 20172017-January , pp.1 - 4

In this study, vibrational resonance phenomena is investigated in excitable neuron population. Synapses where complex electrochemical events take place in is modelled dynamically, not statically by contrast with early studies. Effect of short-Term synaptic depression which is a prominent feature of dynamic synapses on vibrational resonance is studied. The results of numerical simulations that silencing effect of shortterm depression emerges in the cases where static synapses lead to vibrational resonance. © 2017 IEEE.

Effects of astrocytes on neuronal dynamics

Erkan, Yasemin | Özer, Mahmut | Yılmaz, Ergin

Proceedings | 2017 | 2017 Medical Technologies National Conference, TIPTEKNO 20172017-January , pp.1 - 4

Astrocytes are star-shaped glia cells and the most common cell type in the human brain with neurons. Astrocytes fulfill many functions in human brain. Providing support to the cells of the blood-brain barrier, balancing the extracellular ion concentration, supplying nutrients to the nerve tissue, and controlling the development of nerve cells are some of these tasks. In this study, the effects of calcium (Ca2+) ion concentration oscillations occuring in astrocytes on the neuron firing dynamics are investigated. When the obtained results are examined, it is observed that the production rate of insole 1,4,5-Triphosphate (IP3), which i . . .s an agent that triggers calcium release from the resoruces in astrocytes, and the degradation time of that within the cell are important effects on the spike production dynamics of the neuron in contact with astrocyte. It is determined that neurons without any stimulation continue to produce spikes through calcium oscillations in the astrocytes, at high IP3 production rates and longer IP3 degradation times. © 2017 IEEE Daha fazlası Daha az

Effects of inhibitory autapse on the weak signal detection of Hodgkin-Huxley Neuron

Baysal, Veli | Özer, Mahmut | Yılmaz, Ergin

Proceedings | 2017 | 2017 Medical Technologies National Conference, TIPTEKNO 20172017-January , pp.1 - 4

In this paper, the effects of autapse (a kind of synapse formed between the axon or soma of a neuron and its own dendrites) on the weak signal detection capacity of a Hodgkin-Huxley (H-H) neuron are investigated. In the study, we consider that the H-H neuron has an inhibitory autapse modeled as a chemical synapse. The subthreshold sine wave is injected to the H-H neuron as a weak signal. Obtained results indicate that inhibitory autapse prominently increases the weak signal detection capacity of a H-H neuron when the proper autaptic time delay and autaptic conductance values are choosen. © 2017 IEEE.

Classification of diabetic retinopathy disease from Video-Oculography (VOG) signals with feature selection based on C4.5 decision tree

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

Proceedings | 2017 | 2017 Medical Technologies National Conference, TIPTEKNO 20172017-January , pp.1 - 4

'Diabetes Mellitus (Diabetes)' is a disease based on insulin hormone disorders secreted from the pancreas gland. Clinical findings find out that diabetes causes some diseases in vital organs. 'Diabetic Retinopathy' is one of the most common eye diseases based on diabetes, and it is the leading cause of visual loss resulting from structural changes in the retinal vessels. Recent researches show that signals from vital organs can be used to diagnose diseases in the literature. In this study, the features of horizontal and vertical Video-Oculography (VOG) signals from right and left eye are used to classify non-proliferative and prolif . . .erative diabetic retinopathy disease. 25 statistical features are obtained using discrete wavelet transform with VOG signals from 24 subjects. Feature selection is performed using C4.5 decision tree algorithm from 25 features obtained. The statistical features obtained from C4.5 decision tree and discrete wavelet transform are applied as input to artificial neural networks and the classification performance of the 'Diabetic Retinopathy' disease are compared according to these two methods. Our results show that feature selection by C4.5 decision tree algorithm (96.87%) provides better classification performance than feature extraction with discrete wavelet transform (93.75%). © 2017 IEEE Daha fazlası Daha az

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