A model of the starburst amacrine cell for motion direction detection Online publication date: Thu, 27-Apr-2023
by Fenggang Yuan; Hiroyoshi Todo; Cheng Tang; Zheng Tang; Yuki Todo
International Journal of Bio-Inspired Computation (IJBIC), Vol. 21, No. 2, 2023
Abstract: The mechanism of motion direction detection for direction selective ganglion cells (DSGCs) is still not well-understood and under debate. Recent studies have elaborated the critical experimental evidence that the starburst amacrine cells (SACs) can trigger off the null-direction inhibition to DSGCs. In this study, a simple but effective neural model is introduced for the SACs to solve the motion direction detection problems, based on greyscale images in the visual scene. Virtual simulations demonstrate that the neural model is capable of detecting the motion direction of objects with different shapes, sizes, greyscales, and positions efficiently. To further demonstrate the feasibility and effectiveness of the model, the performance of the proposed model is compared with traditional artificial neural networks (ANNs). Experimental results show it can completely beat ANNs on motion direction detection problems, in terms of recognition accuracy, noise immunity, computational and learning costs, biological soundness, and reasonability.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Bio-Inspired Computation (IJBIC):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com