Science in China Series C: Life Sciences

, Volume 44, Issue 5, pp 469–478 | Cite as

A neural network model on self-organizing emergence of simple-cell receptive field with orientation selectivity in visual cortex

  • Qian Yang
  • Xianglin Qi
  • Yunjiu Wang


In order to probe into the self-organizing emergence of simple cell orientation selectivity, we tried to construct a neural network model that consists of LGN neurons and simple cells in visual cortex and obeys the Hebbian learning rule. We investigated the neural coding and representation of simple cells to a natural image by means of this model. The results show that the structures of their receptive fields are determined by the preferred orientation selectivity of simple cells. However, they are also decided by the emergence of self-organization in the unsupervision learning process. This kind of orientation selectivity results from dynamic self-organization based on the interactions between LGN and cortex.


receptive field orientation selectivity dynamic self-organization neural sparse coding unsupervision learning 


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Copyright information

© Science in China Press 2001

Authors and Affiliations

  1. 1.Laboratory of Visual Information Processing, Institute of BiophysicsChinese Academy of SciencesBeijingChina

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