Competition between ON and OFF Neural Pathways Enhancing Collision Selectivity

Lei, Fang, Peng, Zhiping, Cutsuridis, Vassilis , Liu, Mei, Zhang, Yicheng and Yue, Shigang (2020) Competition between ON and OFF Neural Pathways Enhancing Collision Selectivity. In: IEEE WCCI 2020-IJCNN regular session, 19-24 July 2020.

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Abstract

The LGMD1 neuron of locusts shows strong looming-sensitive property for both light and dark objects. Although a few LGMD1 models have been proposed, they are not reliable to inhibit the translating motion under certain conditions compare to the biological LGMD1 in the locust. To address this issue, we propose a bio-plausible model to enhance the collision selectivity by inhibiting the translating motion. The proposed model contains three parts, the retina to lamina layer for receiving luminance change signals, the lamina to medulla layer for extracting motion cues via ON and OFF pathways separately, the medulla to lobula layer for eliminating translational excitation with neural competition. We tested the model by synthetic stimuli and real physical stimuli. The experimental results demonstrate that the proposed LGMD1 model has a strong preference for objects in direct collision course-it can detect looming objects in
different conditions while completely ignoring translating objects.

Keywords:LGMD1 neuron, neural competition, ON and OFF pathways, translating motion, inhibition
Subjects:G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:College of Science > School of Computer Science
ID Code:41701
Deposited On:21 Oct 2020 12:51

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