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Single-Transistor Neuron with Excitatory-Inhibitory Spatiotemporal Dynamics Applied for Neuronal Oscillations.

Accepted version
Peer-reviewed

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Type

Article

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Authors

Li, Hanxi 
Hu, Jiayang 
Chen, Anzhe 
Wang, Chenhao 
Chen, Li 

Abstract

Brain-inspired neuromorphic computing systems with the potential to drive the next wave of artificial intelligence demand a spectrum of critical components beyond simple characteristics. An emerging research trend is to achieve advanced functions with ultracompact neuromorphic devices. In this work, a single-transistor neuron is demonstrated that implements excitatory-inhibitory (E-I) spatiotemporal integration and a series of essential neuron behaviors. Neuronal oscillations, the fundamental mode of neuronal communication, that construct high-dimensional population code to achieve efficient computing in the brain, can also be demonstrated by the neuron transistors. The highly scalable E-I neuron can be the basic building block for implementing core neuronal circuit motifs and large-scale architectural plans to replicate energy-efficient neural computations, forming the foundation of future integrated neuromorphic systems.

Description

Keywords

2D materials, neuromorphic devices, neuronal oscillations, single-transistor neurons, Artificial Intelligence, Neural Networks, Computer, Neurons

Journal Title

Adv Mater

Conference Name

Journal ISSN

0935-9648
1521-4095

Volume Title

Publisher

Wiley