中国物理B ›› 2009, Vol. 18 ›› Issue (12): 5560-5565.doi: 10.1088/1674-1056/18/12/071

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Mechanism for propagation of rate signals through a 10-layer feedforward neuronal network

于婉卿1, 徐定1, 刘锋1, 王炜1, 李捷2   

  1. (1)National Laboratory of Solid State Microstructure and Department of Physics, Nanjing University, Nanjing 210093, China; (2)National Laboratory of Solid State Microstructure and Department of Physics, Nanjing University, Nanjing 210093, China;State Key Laboratory of Pharmaceutical Biotechnology and School of Life, Nanjing University, Nanjing 210093, China
  • 收稿日期:2008-08-17 修回日期:2009-03-05 出版日期:2009-12-20 发布日期:2009-12-20
  • 基金资助:
    Project supported by the National Natural Science Foundation of China (Grant No 10614028), the National Key Basic Research Program of China (Grant No 2007CB814806), and Program for New Century Excellent Talents in University of the Ministry of Education o

Mechanism for propagation of rate signals through a 10-layer feedforward neuronal network

Li Jie(李捷)a)b),Yu Wan-Qing(于婉卿)a), Xu Ding(徐定)a), Liu Feng(刘锋)a)†,andWang Wei(王炜)a)   

  1. a National Laboratory of Solid State Microstructure and Department of Physics, Nanjing University, Nanjing 210093, China; b State Key Laboratory of Pharmaceutical Biotechnology and School of Life, Nanjing University, Nanjing 210093, China
  • Received:2008-08-17 Revised:2009-03-05 Online:2009-12-20 Published:2009-12-20
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant No 10614028), the National Key Basic Research Program of China (Grant No 2007CB814806), and Program for New Century Excellent Talents in University of the Ministry of Education o

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摘要： Using numerical simulations, we explore the mechanism for propagation of rate signals through a 10-layer feedforward network composed of Hodgkin--Huxley (HH) neurons with sparse connectivity. When white noise is afferent to the input layer, neuronal firing becomes progressively more synchronous in successive layers and synchrony is well developed in deeper layers owing to the feedforward connections between neighboring layers. The synchrony ensures the successful propagation of rate signals through the network when the synaptic conductance is weak. As the synaptic time constant τsyn varies, coherence resonance is observed in the network activity due to the intrinsic property of HH neurons. This makes the output firing rate single-peaked as a function of τsyn, suggesting that the signal propagation can be modulated by the synaptic time constant. These results are consistent with experimental results and advance our understanding of how information is processed in feedforward networks.

Abstract: Using numerical simulations, we explore the mechanism for propagation of rate signals through a 10-layer feedforward network composed of Hodgkin--Huxley (HH) neurons with sparse connectivity. When white noise is afferent to the input layer, neuronal firing becomes progressively more synchronous in successive layers and synchrony is well developed in deeper layers owing to the feedforward connections between neighboring layers. The synchrony ensures the successful propagation of rate signals through the network when the synaptic conductance is weak. As the synaptic time constant $\tau_{\rm syn}$ varies, coherence resonance is observed in the network activity due to the intrinsic property of HH neurons. This makes the output firing rate single-peaked as a function of $\tau_{\rm syn}$, suggesting that the signal propagation can be modulated by the synaptic time constant. These results are consistent with experimental results and advance our understanding of how information is processed in feedforward networks.

Key words: feedforward network, synchrony, rate coding, Hodgkin--Huxley model

中图分类号:  (Neuroscience)

  • 87.19.L-
87.10.-e (General theory and mathematical aspects) 87.18.Sn (Neural networks and synaptic communication)