Optoelectronic graded neurons for bioinspired in-sensor motion perception

Motion processing has proven to be a computational challenge and demands considerable computational resources. Contrast this with the fact that flying insects can agilely perceive real-world motion with their tiny vision system. Here we show that phototransistor arrays can directly perceive different types of motion at sensory terminals, emulating the non-spiking graded neurons of insect vision systems. The charge dynamics of the shallow trapping centres in MoS₂ phototransistors mimic the characteristics of graded neurons, showing an information transmission rate of 1,200 bit s^-1 and effectively encoding temporal light information. We used a 20 × 20 photosensor array to detect trajectories in the visual field, allowing the efficient perception of the direction and vision saliency of moving objects and achieving 99.2% recognition accuracy with a four-layer neural network. By modulating the charge dynamics of the shallow trapping centres of MoS₂, the sensor array can recognize motion with a temporal resolution ranging from 10¹ to 10⁶ ms.