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Updated: Aug 23, 2025

Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
Published on: June 24, 2015
A Vertical Single Transistor Neuron with Core-Shell Dual-Gate for Excitatory-Inhibitory Function and Tunable Firing
Taegoon Lee1, Seung-Bae Jeon2, Daewon Kim1
1Department of Electronic Engineering, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin 17104, Korea.
A new transistor neuron device with tunable firing properties was developed. This core-shell dual-gate nanowire neuron enables adaptable learning and error correction in artificial neural networks.
Area of Science:
- Neuromorphic Engineering
- Solid-State Electronics
- Artificial Intelligence Hardware
Background:
- Developing efficient artificial neuron devices is crucial for advancing neuromorphic computing.
- Existing neuron models often lack the flexibility for complex learning rules and error compensation.
Purpose of the Study:
- To realize and verify a novel, multi-functional vertical nanowire single transistor neuron device.
- To demonstrate the device's capability for tunable firing threshold voltage and inhibition.
- To validate system-level performance for applications like pattern recognition.
Main Methods:
- Device fabrication and characterization using Technology Computer-Aided Design (TCAD) simulations.
- Independent control of core and shell gates for distinct functionalities.
- System-level validation through SPICE simulations of a letter recognition task.
Main Results:
- Successful realization of a core-shell dual-gate (CSDG) nanowire neuron.
- Demonstrated tunable firing threshold voltage and inhibition via independent gate control.
- Achieved myelination function for transmission rate control and successful letter recognition.
Conclusions:
- The CSDG NW neuron device offers multi-functional capabilities for advanced SNN hardware.
- This technology contributes to constructing high-density monolithic SNNs.
- The device's adaptability supports robust learning and error correction in AI systems.
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