Cognitive Neurodynamics

, Volume 9, Issue 3, pp 265–277 | Cite as

A neural network model of reliably optimized spike transmission

Review Paper

Abstract

We studied the detailed structure of a neuronal network model in which the spontaneous spike activity is correctly optimized to match the experimental data and discuss the reliability of the optimized spike transmission. Two stochastic properties of the spontaneous activity were calculated: the spike-count rate and synchrony size. The synchrony size, expected to be an important factor for optimization of spike transmission in the network, represents a percentage of observed coactive neurons within a time bin, whose probability approximately follows a power-law. We systematically investigated how these stochastic properties could matched to those calculated from the experimental data in terms of the log-normally distributed synaptic weights between excitatory and inhibitory neurons and synaptic background activity induced by the input current noise in the network model. To ensure reliably optimized spike transmission, the synchrony size as well as spike-count rate were simultaneously optimized. This required changeably balanced log-normal distributions of synaptic weights between excitatory and inhibitory neurons and appropriately amplified synaptic background activity. Our results suggested that the inhibitory neurons with a hub-like structure driven by intensive feedback from excitatory neurons were a key factor in the simultaneous optimization of the spike-count rate and synchrony size, regardless of different spiking types between excitatory and inhibitory neurons.

Keywords

Spike transmission Power-law-distributed synchrony  Log-normally distributed synaptic weights Synaptic background activity 

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Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Toshikazu Samura
    • 1
  • Yuji Ikegaya
    • 2
  • Yasuomi D. Sato
    • 3
    • 4
  1. 1.Department of Applied Molecular Bioscience, Graduate School of MedicineYamaguchi UniversityYamaguchiJapan
  2. 2.Laboratory of Chemical Pharmacology, Graduate School of Pharmaceutical SciencesThe University of TokyoTokyoJapan
  3. 3.Frankfurt Institute for Advanced Studies (FIAS)Goethe University FrankfurtFrankfurt am MainGermany
  4. 4.Institute of Industrial ScienceThe University of TokyoTokyoJapan

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