Synchronous dynamics in neural system coupled with memristive synapse
- 231 Downloads
To study the collective behavior and the regulation mechanism of memristor, the Hindmarsh–Rose neuron cells are selected as the units to construct a coupled system by using the cubic flux-controlled memristor as a connecting synapses, both the firing mode and synchronous behavior in this coupled system are investigated. In this paper, a coefficient is introduced to describe the effect of electromagnetic induction of membrane potential, and the weights of synaptic connection between cells are selected as an adjustable parameter. We have found that, on the one hand, for the certain external current, the firing pattern of neurons could maintain normal state induced by proper electromagnetic induction, and the transition between different firing states could also be observed. On the other hand, both the synchronous effects could be effectively enhanced and the domain of synchronous parameters could be also expanded by tuning the electromagnetic parameters. Particularly, when the coupled system is in the synchronization state, one can see that the firing behavior of neurons will simultaneously change with the varying of the memristance. The similar phenomenon could also be found by introducing the external stimulus signal with a certain frequency. It means that the plasticity of biological synapses could be effectively mimicked by using the memristive synapse and thus the effective memory function of the memristor to the external stimulus signal may be realized. Above results may not only provide some useful clues for understanding the dynamic behavior of neural system coupled with memristive synapses, but also afford us some inspiration to simulate human brain memory, forgetting or some other functions by using the memristor neural network in the future.
KeywordsMemristive synapse HR neuron Electromagnetic induction Synchronous dynamics Firing pattern transition
The project supported by the Natural Science Foundation of Anhui Province, China (No. 1508085MA15), the Key project of cultivation of leading talents in Universities of Anhui Province (No. gxbjZD2016014), the Innovation and practice research project of graduate students of Anhui Normal University, China (No. 2017cxsj045), and the project of Academic and technical leaders candidate of Anhui Province (2017H117).
Compliance with ethical standards
Conflict of interest
The authors have declared that no competing interests exist. These authors contributed equally to this work.
- 9.Wang, Z.Q., Xu, Y., Yang, H.: Lévy noise induced stochastic resonance in an FHN model. Sci. China Technol. Sci 59, 371–375 (2016)Google Scholar
- 11.Chua, L.: Memristor—the missing circuit element. IEEE Trans. Circuits Syst. 18, 507–519 (1971)Google Scholar
- 27.Corinto, F., Ascoli, A., Lanza, V., et al.: Memristor synaptic dynamics’ influence on synchronous behavior of two Hindmarsh–Rose neurons. In: The 2011 International Joint Conference on Neural Networks (IJCNN), pp. 2403–2408. IEEE (2011)Google Scholar
- 28.Ascoli, A., Tetzlaff, R., Lanza, V., et al.: Synchronization properties of a bio-inspired neural network. In: 2015 IEEE 15th International Conference on Nanotechnology (IEEE-NANO), pp. 621–624. IEEE (2015)Google Scholar
- 41.Wang, H.X., Lu, Q.S., Wang, Q.Y.: Complete synchronization in coupled chaotic HR neurons with symmetric coupling schemes. Chin. Phys. Lett. 22, 2173 (2005)Google Scholar