重叠感受野间隙耦合的方向差分运动感知神经网络OA

Cognitive neuroscience studies have found that there are direction differential neurons(object motion selective and direction selective,OMS-DS)in the vertebrate retina,which have the visual neural response property of local-global direction difference preference,with help to distinguish the motion difference between foreground localization and background globalization in a dynamic visual scene.However,few computational models of this neural property have been reported in studies of visual motion perception.To address this problem,a directional differential motion perception neural network(dirDMPNN)is proposed based on the salamander retinal differential motion response properties.The proposed neural network contains both presynaptic and postsynaptic parts.The presynaptic network perceives low-order visual cues triggered by motion changes in the visual field domain;the postsynaptic network realizes the response output based on the gap-junction coupling mechanism of overlapping receptive field to deferentially discriminate foreground and background directions.Systematic experimental studies show that the dirDMPNN perceives foreground-background direction motion cues from translation self-motion in the visual field domain and outputs strong neural spike responses to its differential motion patterns.This paper is inspired by the neural mechanisms of the biological visual brain and focuses on visual information processing.It offers novel insights and methods for addressing motion perception and recognition,target detection and tracking in self-motion visual scenarios,such as those encountered in autonomous environments including spacecraft,autonomous driving,and robotic navigation.