Brain-inspired flexible neuromorphic devices are of great significance for next-generation high-efficiency wearable sensing and computing systems. In this paper, we propose a flexible organic electrochemical transistor using poly[(bithiophene)-alternate-(2,5-di(2-octyldodecyl)- 3,6-di(thienyl)-pyrrolyl pyrrolidone)] (DPPT-TT) as the organic semiconductor and poly(methyl methacrylate) (PMMA)/LiClO₄ solid-state electrolyte as the gate dielectric layer. Under gate voltage modulation, an electric double layer (EDL) forms between the dielectric layer and the channel, allowing the device to operate at low voltages. Furthermore, by leveraging the double layer effect and electrochemical doping within the device, we successfully mimic various synaptic behaviors, including excitatory post-synaptic currents (EPSC), paired-pulse facilitation (PPF), high-pass filtering characteristics, transitions from short-term plasticity (STP) to long-term plasticity (LTP), and demonstrate its image recognition and storage capabilities in a 3 × 3 array. Importantly, the device’s electrical performance remains stable even after bending, achieving ultra-low-power consumption of 2.08 fJ per synaptic event at −0.001 V. This research may contribute to the development of ultra-low-power neuromorphic computing, biomimetic robotics, and artificial intelligence.

The energy-efficient perceptual capabilities of the human visual system have inspired the development of optoelectronic neuromorphic devices to replicate the essential properties. Color vision that is highly important for perception and cognitive behaviors, such as object recognition, esthetics, and communication, has recently been reported based on optoelectronic neuromorphic devices. The responses to different wavelengths of light are mainly dependent on power density, whereas the eye recognizes color images based on luminosity. This Letter presents a quantum dots (QDs) modified InGaZnO (IGZO) synaptic transistor based on an IGZO/CdS-QDs/PMMA heterojunction. These IGZO-based synapses show significant responsivity to 655-nm light through the spectrum broadening by QDs. More importantly, luminance-based color-to-gray conversion can be realized with this device using a spike encoding scheme, transforming color images into grayscale in parallel. Notably, the QDs modified IGZO-based synapses demonstrated a remarkable 34.3% improvement in recognition accuracy on the multicolor MNIST dataset in comparison with the pristine devices. Our results indicate that this visible-light responsive IGZO-based synapse has great potential for endowing the neuromorphic visual system with enhanced color vision and provides a biologically plausible approach for color-to-gray conversion.