Frontiers in Computational Neuroscience (Jul 2020)

Necessary Conditions for Reliable Propagation of Slowly Time-Varying Firing Rate

  • Navid Hasanzadeh,
  • Navid Hasanzadeh,
  • Mohammadreza Rezaei,
  • Mohammadreza Rezaei,
  • Sayan Faraz,
  • Milos R. Popovic,
  • Milos R. Popovic,
  • Milad Lankarany,
  • Milad Lankarany,
  • Milad Lankarany

DOI
https://doi.org/10.3389/fncom.2020.00064
Journal volume & issue
Vol. 14

Abstract

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Reliable propagation of slow-modulations of the firing rate across multiple layers of a feedforward network (FFN) has proven difficult to capture in spiking neural models. In this paper, we explore necessary conditions for reliable and stable propagation of time-varying asynchronous spikes whose instantaneous rate of changes—in fairly short time windows [20–100] msec—represents information of slow fluctuations of the stimulus. Specifically, we study the effect of network size, level of background synaptic noise, and the variability of synaptic delays in an FFN with all-to-all connectivity. We show that network size and the level of background synaptic noise, together with the strength of synapses, are substantial factors enabling the propagation of asynchronous spikes in deep layers of an FFN. In contrast, the variability of synaptic delays has a minor effect on signal propagation.

Keywords