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.
Keywords: 2D materials; neuromorphic devices; neuronal oscillations; single-transistor neurons.
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