Charge-trap transistors are widely used for the simulation of biological synaptic functions. However, the unique structure of silicon–oxide–nitride–oxide–silicon (SONOS) makes it difficult to simulate short-term memory (STM). Based on simulation modeling, this work proposes a cylindrical surrounding double-gate (CSDG) nanowire synaptic transistor with a Si \(_3\) N \(_4\) charge trap layer in direct contact with the channel. The synaptic functions of the enhanced weights are mimicked by modulating electrical impulses to achieve the short-term potentiation (STP) to long-term potentiation (LTP) transition. In addition, the post-synaptic response changes with light intensity and wavelength under light illumination, which is phenomenologically similar to light-assisted dopamine-promoted synaptic activity. Furthermore, the high blue light responsiveness successfully exhibits the physiological characteristic that blue light promotes more dopamine secretion in the retina of the human eye. This model introduces additional light stimulation to achieve dopamine dynamics driven learning acceleration, providing a foundation for improving the rapid recognition and learning ability of neural computing systems in the next step.
