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

Navid Hasanzadeh; Mohammadreza Rezaei; Sayan Faraz; Milos R Popovic; Milad Lankarany

doi:10.3389/fncom.2020.00064

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

Front Comput Neurosci. 2020 Jul 29:14:64. doi: 10.3389/fncom.2020.00064. eCollection 2020.

Authors

Navid Hasanzadeh^{1

2}, Mohammadreza Rezaei^{1

3}, Sayan Faraz¹, Milos R Popovic^{3

4}, Milad Lankarany^{1

3

4}

Affiliations

¹ Clinical and Computational Neuroscience, Krembil Research Institute, University Health Network, Toronto, ON, Canada.
² School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
³ KITE Research Institute, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada.
⁴ Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada.

Abstract

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: feed-forward neural network; information propagation; network size; noise; synaptic delays; time-varying rate coding.