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Self-organization model on receptive field of neuron with asymmetric time window of synaptic modification

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【Author】 TIAN Jie & LU HuiminLaboratory of Visual Information Processing, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China

【摘要】 <正>The spatial-temporal response properties of some simple neurons in visual pathway arise basically prior to birth. In the absence of visual experience, how do these neurons develop in visual system? Based on Wimbauer network with delay, a four-layer feed-forward network model is proposed, which is characterized by modifying the Hebb learning rule through introducing the asymmetric time window of synaptic modification found recently in neurobiology. The model can not only generate by self-organization more diversified spatial-temporal response characteristics of neu-ronal receptive field than earlier models but also provide some explanations for the possible mechanism underlying the development of receptive fields of contrast polarity sensitive neurons found in visual system of vertebrate. Thus the proposed model may be more widely applicable than Linsker model and Wimbauer model.

【Abstract】 The spatial-temporal response properties of some simple neurons in visual pathway arise basically prior to birth. In the absence of visual experience, how do these neurons develop in visual system? Based on Wimbauer network with delay, a four-layer feed-forward network model is proposed, which is characterized by modifying the Hebb learning rule through introducing the asymmetric time window of synaptic modification found recently in neurobiology. The model can not only generate by self-organization more diversified spatial-temporal response characteristics of neu-ronal receptive field than earlier models but also provide some explanations for the possible mechanism underlying the development of receptive fields of contrast polarity sensitive neurons found in visual system of vertebrate. Thus the proposed model may be more widely applicable than Linsker model and Wimbauer model.

【基金】 Thiswork was supported by the National Natural Science Foundation of China (Grant Nos. 39970185 and 69835002).
  • 【文献出处】 Chinese Science Bulletin ,科学通报(英文版) , 编辑部邮箱 ,2001年12期
  • 【分类号】Q42
  • 【下载频次】14
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