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Section BRAIN-COMPUTER INTERFACES, COGNITIVE NAVIGATION WORKSHOP AND NEUROENGINEERING
Acknowledgements
This work was supported by the Russian Science Foundation under project 15-12-10018. References
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Synchronization of Two Coupled Electronic Neurons via Memristor
S.A Gerasimova*, A.N. Mikhaylov, D.S. Korolev, A.I. Belov, I.N. Antonov, O.N. Gorshkov, V.B. Kazantsev
Lobachevsky University, Nizhny Novgorod, Russia. * Presenting e-mail: gerasimova@neuro.nnov.ru
Design of electronic neuron networks capable to reproduce brain functions in silico is one of the most intriguing challenges in modern science and engineering. Such systems would permit to develop new generation of information processing technologies based on brain computation principles. Another interesting application is to make an interface between electronic circuits and living neurons for biomedicine. The electronic circuits should resemble all dynamical regimes of nerve pulse generation in single neurons. In the network design, the crucial point is synaptic coupling between neurons providing reliable signal transmission. Moreover, the coupling strength can be variable depending on the ongoing neuron activity, what is called synaptic plasticity.
In this work, the dynamics of two electronic neuron oscillators coupled via memristor has been investigated. Each neuron is implemented as pulse signal generator based on the FiteHugh-Nagumo equations. This model provides a qualitative description of the main neurons' characteristics including the excitable and self-oscillatory dynamics. Different neuron-like signals (single pulse, transients, self-oscillations) can be observed by changing threshold parameter. Memristor is realized in a simple metal-oxide-metal nanostructure demonstrating reproducible resistive switching effect [1].
After testing and tuning of the master and slave neuron oscillators their coupling by memristor was implemented. The output signal from the master neuron was conveyed to input of memristor. Output signal from memristor sent to the input of the slave neuron. Such unidirectional signal transmission implements the functionality of excitatory synaptic coupling.
Such model mimics the interaction between synaptically coupled brain neurons, where the memristor imitates neuron axon. The resistance can be continuously varied, and such analog variation of resistance provides a useful model of key features of the biological synapse, and memristor as synapses in neuromorphic circuits can model synaptic plasticity. The synaptic connection is modelled by output signal from memristor. It is experimentally demonstrated that such connection can provide forced synchronization with locking ratios 1:1.
Acknowledgements
The study is supported by the Russian Science Foundation (grant 16-19-00144). References
1. A.N. Mikhaylov, A.I. Belov, D.V. Guseinov et al., Mat. Sci. Eng. B, 2015, 194, 48-54.
OM&P
Opera Med Physiol 2016 Vol. 2 (S1) 77
