Institute of Biology and Biomedicine, National Research Lobachevsky State University of Nizhny Novgorod, 603950 Nizhny Novgorod, Russia.
Research Institute and Technology, National Research Lobachevsky State University of Nizhny Novgorod, 603950 Nizhny Novgorod, Russia.
Sensors (Basel). 2021 Aug 19;21(16):5587. doi: 10.3390/s21165587.
We propose a memristive interface consisting of two FitzHugh-Nagumo electronic neurons connected via a metal-oxide (Au/Zr/ZrO(Y)/TiN/Ti) memristive synaptic device. We create a hardware-software complex based on a commercial data acquisition system, which records a signal generated by a presynaptic electronic neuron and transmits it to a postsynaptic neuron through the memristive device. We demonstrate, numerically and experimentally, complex dynamics, including chaos and different types of neural synchronization. The main advantages of our system over similar devices are its simplicity and real-time performance. A change in the amplitude of the presynaptic neurogenerator leads to the potentiation of the memristive device due to the self-tuning of its parameters. This provides an adaptive modulation of the postsynaptic neuron output. The developed memristive interface, due to its stochastic nature, simulates a real synaptic connection, which is very promising for neuroprosthetic applications.
我们提出了一种由两个通过金属氧化物（Au/Zr/ZrO(Y)/TiN/Ti）忆阻突触器件连接的 FitzHugh-Nagumo 电子神经元组成的忆阻接口。我们基于商业数据采集系统创建了一个软硬件复合体，该系统记录由前一个电子神经元产生的信号，并通过忆阻器件将其传输到后一个神经元。我们通过数值和实验证明了包括混沌和不同类型的神经同步在内的复杂动力学。与类似设备相比，我们系统的主要优势在于其简单性和实时性能。由于参数的自调整，前一个神经发生器的幅度变化会导致忆阻器件的增强，从而实现对后一个神经元输出的自适应调制。由于其随机性，开发的忆阻接口模拟了真实的突触连接，这对于神经假肢应用非常有前途。
