Yazar "Tekin R." seçeneğine göre listele

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    Complexity and irregularity analysis of the output data of a cortical network
    (2013) Tekin R.; Emin Tagluk M.; Ertugrul Ö.F.; Sezgin N.
    Depending on the complex interconnection of billions of neurons forming cortical network excitation times and the emergence of action potentials or spike trains becomes complex and irregular. The effect of various parameters such as synaptic connections, conductivity and voltage dependent channels on the output of the network has become of research issues. In this study, based on Hodgkin-Huxley neuron model an artificial cortical network that simulates a local region of cortex was designed and the effect of probabilistic values of network parameters used in this model on irregularity and complexity of the spike trains at the neurons' output were investigated. Approximation Entropy, Spectral Entropy and Magnitude Squared Coherence methods were used for irregularity analysis. © 2013 IEEE.
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    Effect of external stimulus and ionic concentrations on Hodgkin-Huxley neural model
    (2012) Tekin R.; Ta?luk M.E.; Ertu?rul O.F.
    Hodgkin-Huxley (HH) neuron model has an important place in theoretical neuroscience. In the study, on the basis of HH neuron model, the effects of ionic sodium and potassium concentrations as well as the effect of excitation current density on AP were investigated. It was found that while sodium concentration predominantly affects the amplitude of AP, Potassium concentration affects the threshold and hyper-polarization levels. It was observed that the increase in excitation current level cause to early triggering of AP which leads to increase the AP/sec rate. This information may be used in theoretical neuroscience. © 2012 IEEE.
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    Kortikal spindle salinim aktivitesinin oluşumunda ve senkronizasyonunda talamik projeksiyonlarin rolünün model temelli incelenmesi
    (Institute of Electrical and Electronics Engineers Inc., 2017) Tekin R.; Kaya Y.; Sezgin N.; Ta?luk M.E.
    In this study, mechanisms of formation of thalamocortical spindle oscillations, which are critical for various functions of the brain, have been examined on a model basis. For this, both spike activity and spectral characteristics were investigated by isolating the cortex and thalamus and then connecting them with thalamo-cortical projections. In order to determine the spindle activity in the LFP signal of each cell group, it has been tried to determine slow-wave and spindle frequency components which can coexist with each other on the basis of superposition. For this purpose, power spectral densities of LFP signals were analyzed. According to the results of this study, spindle activity can be seen in thalamus without cortex. It can be said that thalamo-cortical projections provided by the thalamic TC cells enable the spindle activity to be transferred into the cortex and thus display itself in LFP / EEG. At the same time, it has been observed that thalamo-cortical projections increase spike activity, equalize the dominant frequency in the whole system, and also cortico-thalamic projections strengthen spindle activity. © 2017 IEEE.
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    Separation of EEG signals by using independent component analysis
    (2012) Sezgin N.; Ta?luk M.E.; Tekin R.
    Independent Component Analysis (ICA) is a statistical method used for separating nongaussian independent components of a mixture signal. In this study, by separating the signal into its possible independent components, the simplification and comprehension of analysis of EEG signals was aimed. Through such an analysis it was thought that early diagnosis of some neurological disease such as epilepsy, parkinson's disease, sleep disorders as well as information regarding the location and size of problematic zone may become possible. © 2012 IEEE.