High-capacity embedding of synfire chains in a cortical network model

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• 作者：Chris Trengove (1) (2) (3) (4)
  Cees van Leeuwen (2) (4)
  Markus Diesmann (3) (5)
  
• 关键词：Recurrent network dynamics ; Feedforward network ; Synchrony ; Synaptic conductance ; Synfire chain ; Storage capacity
• 刊名：Journal of Computational Neuroscience
• 出版年：2013
• 出版时间：April 2013
• 年：2013
• 卷：34
• 期：2
• 页码：185-209
• 全文大小：2684KB
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• 作者单位：Chris Trengove (1) (2) (3) (4)
  Cees van Leeuwen (2) (4)
  Markus Diesmann (3) (5)
  
  1. Integrated Simulation of Living Matter Group, RIKEN, Computational Science Research Program, Wako, Saitama, Japan
  2. Laboratory for Perceptual Dynamics, RIKEN, Brain Science Institute, Wako, Saitama, Japan
  3. Laboratory for Computational Neurophysics, RIKEN, Brain Science Institute, Wako, Saitama, Japan
  4. Perceptual Dynamics Laboratory, University of Leuven, Tiensestraat 102, 3000, Leuven, Belgium
  5. Institute of Neuroscience and Medicine, Computational and Systems Neuroscience (INM-6), Research Center Juelich, Juelich, Germany
  
• ISSN：1573-6873

文摘

Synfire chains, sequences of pools linked by feedforward connections, support the propagation of precisely timed spike sequences, or synfire waves. An important question remains, how synfire chains can efficiently be embedded in cortical architecture. We present a model of synfire chain embedding in a cortical scale recurrent network using conductance-based synapses, balanced chains, and variable transmission delays. The network attains substantially higher embedding capacities than previous spiking neuron models and allows all its connections to be used for embedding. The number of waves in the model is regulated by recurrent background noise. We computationally explore the embedding capacity limit, and use a mean field analysis to describe the equilibrium state. Simulations confirm the mean field analysis over broad ranges of pool sizes and connectivity levels; the number of pools embedded in the system trades off against the firing rate and the number of waves. An optimal inhibition level balances the conflicting requirements of stable synfire propagation and limited response to background noise. A simplified analysis shows that the present conductance-based synapses achieve higher contrast between the responses to synfire input and background noise compared to current-based synapses, while regulation of wave numbers is traced to the use of variable transmission delays.