New Mechanism of Visual Motion Direction Detection Based on McCulloch-Pitts Neuron Model

Yi Chen, Zheng Tang, Hiroyoshi Todo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Research on the detection mechanism of visual system for object motion direction is of great significance to improve our understanding of both biological vision and the human brain. In this study, we propose a new mechanism to detect motion direction based on McCulloch-Pitts model of neuron. We first propose a local motion direction detection neuron based on McCulloch-Pitts model of neuron, and apply it to the receptive field inputs of two-dimensional photoreceptors. The outputs of the all local motion direction detective neurons in the corresponding region is measured and are used to infer the global motion direction. The effectiveness of the mechanism is verified by computer simulation which shows that the mechanism can detect the movement direction of an object regardless of the shape, size and position of the object, which is consistent with most known physiological experimental results.

Original languageEnglish
Title of host publication2021 4th International Conference on Artificial Intelligence and Big Data, ICAIBD 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages448-453
Number of pages6
ISBN (Electronic)9780738131702
DOIs
StatePublished - 2021/05/28
Event4th International Conference on Artificial Intelligence and Big Data, ICAIBD 2021 - Chengdu, China
Duration: 2021/05/282021/05/31

Publication series

Name2021 4th International Conference on Artificial Intelligence and Big Data, ICAIBD 2021

Conference

Conference4th International Conference on Artificial Intelligence and Big Data, ICAIBD 2021
Country/TerritoryChina
CityChengdu
Period2021/05/282021/05/31

Keywords

  • McCulloch-Pitts model
  • motion direction detection
  • neuron

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management
  • Decision Sciences (miscellaneous)
  • Safety, Risk, Reliability and Quality

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