A model of amacrine cells for orientation detection

Fenggang Yuan; Cheng Tang; Zheng Tang; Yuki Todo; Fenggang Yuan; Cheng Tang; Zheng Tang; Yuki Todo

doi:10.3934/era.2023103

Electronic Research Archive

2023, Volume 31, Issue 4: 1998-2018. doi: 10.3934/era.2023103

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Research article Special Issues

A model of amacrine cells for orientation detection

1.
Faculty of Engineering, University of Toyama, Toyama 930-8555, Japan
2.
Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan
3.
Faculty of Electrical and Computer Engineering, Kanazawa University, Kanazawa 920-1192, Japan

Received: 13 November 2022 Revised: 24 December 2022 Accepted: 31 January 2023 Published: 16 February 2023

As the most studied sensory system, the visual system plays an important role in our understanding of brain functions. Biological researchers have divided the nerve cells in the retina into dozens of visual channels carrying various characteristics based on visual features. Although orientation-selective cells have been identified in the retinas of various animals, the specific neural circuits of such cells have been controversial. In this study, a new simple and efficient orientation detection model based on the perceptron is proposed to restore the neural circuitry of orientation-selective cells in the retina. The performance of this model is experimentally compared with that of the convolutional neural network for image orientation recognition, and the results verify that the proposed model offers very good orientation detection. The proposed perceptron-based orientation detection model provides a new perspective to explain the neural circuits of orientation-selective cells.
- visual system,
- perceptron,
- orientation detection,
- grayscale,
- amacrine cell
Citation: Fenggang Yuan, Cheng Tang, Zheng Tang, Yuki Todo. A model of amacrine cells for orientation detection[J]. Electronic Research Archive, 2023, 31(4): 1998-2018. doi: 10.3934/era.2023103

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Abstract

As the most studied sensory system, the visual system plays an important role in our understanding of brain functions. Biological researchers have divided the nerve cells in the retina into dozens of visual channels carrying various characteristics based on visual features. Although orientation-selective cells have been identified in the retinas of various animals, the specific neural circuits of such cells have been controversial. In this study, a new simple and efficient orientation detection model based on the perceptron is proposed to restore the neural circuitry of orientation-selective cells in the retina. The performance of this model is experimentally compared with that of the convolutional neural network for image orientation recognition, and the results verify that the proposed model offers very good orientation detection. The proposed perceptron-based orientation detection model provides a new perspective to explain the neural circuits of orientation-selective cells.

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