Evaluating the effectiveness of several synchronization control methods applying to the electrically and the chemically coupled hindmarsh-rose neurons


Cimen Z., Korkmaz N. , Altuncu Y., KILIÇ R.

BIOSYSTEMS, cilt.198, 2020 (SCI İndekslerine Giren Dergi) identifier identifier identifier

Özet

This study focuses on the synchronization control between the coupled neurons. The achievements of several synchronization control methods have been checked by evaluating the effects of the synaptic coupling weight alteration on the synchronization. Here, a neural ensemble has been constructed by utilizing the Hindmarsh Rose (HR) Neuron Model. The HR neurons have been linked to each other with the bidirectional coupling. The synchrony or the asynchrony states between these coupled neurons have been observed by using the standard deviation results. Here, firstly, the electrically and the chemically coupled HR neurons have been handled without using any control method, separately and the effects of the synaptic coupling weight alteration on the synchronic firing have been assessed by considering the features of the coupling types. Then, while the electrically coupled HR neurons are generally preferred in the available synchronization control studies; the Lyapunov, the back-stepping, and the feedback synchronization control methods have been adapted to both the electrically and the chemically coupled HR neurons. Thus, a remarkable contribution has been provided to the limited number of studies, which are about the synchronization control of the chemically coupled HR neurons. Also, the synchronization control between the electrically or the chemically coupled HR neurons has been provided by the back-stepping method for the first time. Finally, the differences between the membrane potentials of the coupled neurons have been calculated by utilizing an alternative error function. Since this function calculates the amplitude and the phase errors, separately; the effectiveness of these methods can be evaluated correctly in terms of the performing the minimum differences between the neural dynamics.