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

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 ins...

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Main Authors: Navid Hasanzadeh, Mohammadreza Rezaei, Sayan Faraz, Milos R. Popovic, Milad Lankarany
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-07-01
Series:Frontiers in Computational Neuroscience
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fncom.2020.00064/full
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spelling doaj-6aa169d0ab554b7f920c1d26563cf5c92020-11-25T03:32:43ZengFrontiers Media S.A.Frontiers in Computational Neuroscience1662-51882020-07-011410.3389/fncom.2020.00064539839Necessary Conditions for Reliable Propagation of Slowly Time-Varying Firing RateNavid Hasanzadeh0Navid Hasanzadeh1Mohammadreza Rezaei2Mohammadreza Rezaei3Sayan Faraz4Milos R. Popovic5Milos R. Popovic6Milad Lankarany7Milad Lankarany8Milad Lankarany9Clinical and Computational Neuroscience, Krembil Research Institute, University Health Network, Toronto, ON, CanadaSchool of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, IranClinical and Computational Neuroscience, Krembil Research Institute, University Health Network, Toronto, ON, CanadaKITE Research Institute, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, CanadaClinical and Computational Neuroscience, Krembil Research Institute, University Health Network, Toronto, ON, CanadaKITE Research Institute, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, CanadaInstitute of Biomedical Engineering, University of Toronto, Toronto, ON, CanadaClinical and Computational Neuroscience, Krembil Research Institute, University Health Network, Toronto, ON, CanadaKITE Research Institute, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, CanadaInstitute of Biomedical Engineering, University of Toronto, Toronto, ON, CanadaReliable 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.https://www.frontiersin.org/article/10.3389/fncom.2020.00064/fulltime-varying rate codinginformation propagationfeed-forward neural networknoisenetwork sizesynaptic delays
collection DOAJ
language English
format Article
sources DOAJ
author Navid Hasanzadeh
Navid Hasanzadeh
Mohammadreza Rezaei
Mohammadreza Rezaei
Sayan Faraz
Milos R. Popovic
Milos R. Popovic
Milad Lankarany
Milad Lankarany
Milad Lankarany
spellingShingle Navid Hasanzadeh
Navid Hasanzadeh
Mohammadreza Rezaei
Mohammadreza Rezaei
Sayan Faraz
Milos R. Popovic
Milos R. Popovic
Milad Lankarany
Milad Lankarany
Milad Lankarany
Necessary Conditions for Reliable Propagation of Slowly Time-Varying Firing Rate
Frontiers in Computational Neuroscience
time-varying rate coding
information propagation
feed-forward neural network
noise
network size
synaptic delays
author_facet Navid Hasanzadeh
Navid Hasanzadeh
Mohammadreza Rezaei
Mohammadreza Rezaei
Sayan Faraz
Milos R. Popovic
Milos R. Popovic
Milad Lankarany
Milad Lankarany
Milad Lankarany
author_sort Navid Hasanzadeh
title Necessary Conditions for Reliable Propagation of Slowly Time-Varying Firing Rate
title_short Necessary Conditions for Reliable Propagation of Slowly Time-Varying Firing Rate
title_full Necessary Conditions for Reliable Propagation of Slowly Time-Varying Firing Rate
title_fullStr Necessary Conditions for Reliable Propagation of Slowly Time-Varying Firing Rate
title_full_unstemmed Necessary Conditions for Reliable Propagation of Slowly Time-Varying Firing Rate
title_sort necessary conditions for reliable propagation of slowly time-varying firing rate
publisher Frontiers Media S.A.
series Frontiers in Computational Neuroscience
issn 1662-5188
publishDate 2020-07-01
description 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.
topic time-varying rate coding
information propagation
feed-forward neural network
noise
network size
synaptic delays
url https://www.frontiersin.org/article/10.3389/fncom.2020.00064/full
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