Multi-terminal memristive devices enabling tunable synaptic plasticity in neuromorphic hardware: a mini-review

TL;DR

This mini-review discusses recent advances in multi-terminal memristive devices on silicon that enable tunable heterosynaptic plasticity, highlighting their potential for neuromorphic hardware and compatibility with CMOS technology.

Contribution

It provides an overview of the latest developments in multi-terminal memristive devices for implementing heterosynaptic plasticity in neuromorphic systems.

Findings

Multi-terminal memristive devices enable tunable synaptic plasticity.

These devices are scalable and compatible with CMOS technology.

They facilitate heterosynaptic plasticity in hardware.

Abstract

Neuromorphic computing based on spiking neural networks has the potential to significantly improve on-line learning capabilities and energy efficiency of artificial intelligence, specially for edge computing. Recent progress in computational neuroscience have demonstrated the importance of heterosynaptic plasticity for network activity regulation and memorization. Implementing heterosynaptic plasticity in hardware is thus highly desirable, but important materials and engineering challenges remain, calling for breakthroughs in neuromorphic devices. In this mini-review, we propose an overview of the latest advances in multi-terminal memristive devices on silicon with tunable synaptic plasticity, enabling heterosynaptic plasticity in hardware. The scalability and compatibility of the devices with industrial complementary metal oxide semiconductor (CMOS) technologies are discussed.