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Parylene-based memristive synapses for hardware neural networks capable of dopamine-modulated STDP learning
Journal of Physics D: Applied Physics ( IF 3.4 ) Pub Date : 2021-09-03 , DOI: 10.1088/1361-6463/ac203c
A A Minnekhanov 1 , B S Shvetsov 1, 2 , A V Emelyanov 1, 3 , K Yu Chernoglazov 1 , E V Kukueva 1 , A A Nesmelov 1 , Yu V Grishchenko 1 , M L Zanaveskin 1 , V V Rylkov 1, 4 , V A Demin 1, 3
Affiliation  

Nowadays there is a growing interest in wearable and biocompatible computing systems that are safe for the human body. Memristive devices are prospective for such tasks owing to a number of their attractive properties, in particular, the multilevel character of resistive switching, or plasticity, which allows them to emulate synapses in hardware neuromorphic networks (NNs). The use of local learning rules for such NNs, for example, bioinspired spike-timing-dependent plasticity (STDP), has firmly established itself in recent years. In biological systems the basic STDP can be modified in the presence of neuromodulators (e.g. dopamine). This effect is believed to be essential for important biological functions such as reinforcement learning (RL), memory and others. The goal of this work was to demonstrate that such dopamine-like modulated STDP can be used in memristors based on a biocompatible polymer, parylene (poly-p-xylylene, or PPX). We have studied memristors both in the form of single Cu/PPX/ITO devices and in the form of crossbar Cu/PPX/Au structures. It was found that, in addition to stable memristive characteristics suitable for NNs, these devices can also change their conductance by means of bioinspired STDP rules, including dopamine-like modulated STDP window realized by introducing the coefficients for neuron spike amplitudes. The amplitude coefficients from −1 (inhibitory mode) to 1 (excitatory mode) of pre- and post-spikes, reflecting the ‘dopamine’ concentration, in various combinations allow observing the STDP window not only of the usual shape, but also of the anti-STDP, bell and anti-bell shapes. The obtained results demonstrate that the development of memristors based on PPX provides prospects for hardware realization of bio-inspired spiking NNs with RL ability.



中文翻译:

基于聚对二甲苯的忆阻突触,用于能够进行多巴胺调制 STDP 学习的硬件神经网络

如今,人们对对人体安全的可穿戴和生物相容性计算系统越来越感兴趣。忆阻器件具有许多吸引人的特性,特别是电阻开关或可塑性的多级特性,这使它们能够模拟硬件神经形态网络 (NN) 中的突触,因此它们有望用于此类任务。近年来,对此类神经网络使用本地学习规则,例如生物启发的尖峰时间依赖性可塑性(STDP),已经稳固地确立了自己的地位。在生物系统中,可以在存在神经调节剂(例如多巴胺)的情况下修改基本 STDP。这种效应被认为对于强化学习 (RL)、记忆等重要的生物功能是必不可少的。这项工作的目标是证明这种类似多巴胺的调制 STDP 可用于基于生物相容性聚合物聚对二甲苯(聚对二甲苯,或 PPX)的忆阻器。我们研究了单个 Cu/PPX/ITO 器件形式和纵横式 Cu/PPX/Au 结构形式的忆阻器。研究发现,除了适用于神经网络的稳定忆阻特性外,这些器件还可以通过仿生 STDP 规则改变其电导,包括通过引入神经元尖峰幅度系数实现的类多巴胺调制 STDP 窗口。从 -1(抑制模式)到 1(兴奋模式)的前峰值和后峰值的幅度系数,反映了“多巴胺”浓度,在各种组合中不仅可以观察到通常形状的 STDP 窗口,还可以观察到反STDP,钟形和反钟形。所得结果表明,基于 PPX 的忆阻器的开发为具有 RL 能力的仿生尖峰神经网络的硬件实现提供了前景。

更新日期:2021-09-03
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