A multilayer neural network model for perception of rotational motion
作者: Aike GuoHaijian SunXianyi Yang
作者单位: 1Institute of Biophysics, Chinese Academy of Sciences
刊名: Science in China Series C: Life Sciences, 1997, Vol.40 (1), pp.90-100
来源数据库: Springer Nature Journal
DOI: 10.1007/BF02879111
关键词: perception of rotational motionoscillating neutral networkself-organized feature map
英文摘要: Abstract(#br)A multilayer neural nerwork model for the perception of rotational motion has been developed using Reichardt’s motion detector array of correlation type, Kohonen’s self-organized feature map and Schuster-Wagner’s oscillating neural network. It is shown that the unsupervised learning could make the neurons on the second layer of the network tend to be self-organized in a form resembling columnar organization of selective directions in area MT of the primate’s visual cortex. The output layer can interpret rotation information and give the directions and velocities of rotational motion. The computer simulation results are in agreement with some psychophysical observations of rotational perception. It is demonstrated that the temporal correlation between the oscillating neurons...
全文获取路径: Springer Nature  (合作)
影响因子:1.61 (2011)

  • motion 运动
  • perception 知觉
  • rotational 转动
  • neural 神经系统的
  • multilayer 多层的
  • network 网络
  • model 模型