Neuronal spike-train responses in the presence of threshold noise

The variability of neuronal firing has been an intense topic of study for many years. From a modelling perspective it has often been studied in conductance based spiking models with the use of additive or multiplicative noise terms to represent channel fluctuations or the stochastic nature of neuro...

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Main Authors: Coombes, Stephen, Thul, Ruediger, Laudanski, Jonathan, Palmer, Alan, Sumner, Chris
Format: Article
Published: Taylor & Francis 2012
Subjects:
Online Access:https://eprints.nottingham.ac.uk/1333/
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author Coombes, Stephen
Thul, Ruediger
Laudanski, Jonathan
Palmer, Alan
Sumner, Chris
author_facet Coombes, Stephen
Thul, Ruediger
Laudanski, Jonathan
Palmer, Alan
Sumner, Chris
author_sort Coombes, Stephen
building Nottingham Research Data Repository
collection Online Access
description The variability of neuronal firing has been an intense topic of study for many years. From a modelling perspective it has often been studied in conductance based spiking models with the use of additive or multiplicative noise terms to represent channel fluctuations or the stochastic nature of neurotransmitter release. Here we propose an alternative approach using a simple leaky integrate-and-fire model with a noisy threshold. Initially, we develop a mathematical treatment of the neuronal response to periodic forcing using tools from linear response theory and use this to highlight how a noisy threshold can enhance downstream signal reconstruction. We further develop a more general framework for understanding the responses to large amplitude forcing based on a calculation of first passage times. This is ideally suited to understanding stochastic mode-locking, for which we numerically determine the Arnol'd tongue structure. An examination of data from regularly firing stellate neurons within the ventral cochlear nucleus, responding to sinusoidally amplitude modulated pure tones, shows tongue structures consistent with these predictions and highlights that stochastic, as opposed to deterministic, mode-locking is utilised at the level of the single stellate cell to faithfully encode periodic stimuli.
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spelling nottingham-13332020-05-04T16:32:45Z https://eprints.nottingham.ac.uk/1333/ Neuronal spike-train responses in the presence of threshold noise Coombes, Stephen Thul, Ruediger Laudanski, Jonathan Palmer, Alan Sumner, Chris The variability of neuronal firing has been an intense topic of study for many years. From a modelling perspective it has often been studied in conductance based spiking models with the use of additive or multiplicative noise terms to represent channel fluctuations or the stochastic nature of neurotransmitter release. Here we propose an alternative approach using a simple leaky integrate-and-fire model with a noisy threshold. Initially, we develop a mathematical treatment of the neuronal response to periodic forcing using tools from linear response theory and use this to highlight how a noisy threshold can enhance downstream signal reconstruction. We further develop a more general framework for understanding the responses to large amplitude forcing based on a calculation of first passage times. This is ideally suited to understanding stochastic mode-locking, for which we numerically determine the Arnol'd tongue structure. An examination of data from regularly firing stellate neurons within the ventral cochlear nucleus, responding to sinusoidally amplitude modulated pure tones, shows tongue structures consistent with these predictions and highlights that stochastic, as opposed to deterministic, mode-locking is utilised at the level of the single stellate cell to faithfully encode periodic stimuli. Taylor & Francis 2012-03-26 Article PeerReviewed Coombes, Stephen, Thul, Ruediger, Laudanski, Jonathan, Palmer, Alan and Sumner, Chris (2012) Neuronal spike-train responses in the presence of threshold noise. Frontiers in Life Science, 5 (3-4). pp. 91-105. ISSN 2155-3769 Integrate-and-fire Arnol'd tongues Stochastic mode-locking Threshold noise First passage times Neural coding http://dx.doi.org/10.1080/21553769.2011.556016 doi:10.1080/21553769.2011.556016 doi:10.1080/21553769.2011.556016
spellingShingle Integrate-and-fire
Arnol'd tongues
Stochastic mode-locking
Threshold noise
First passage times
Neural coding
Coombes, Stephen
Thul, Ruediger
Laudanski, Jonathan
Palmer, Alan
Sumner, Chris
Neuronal spike-train responses in the presence of threshold noise
title Neuronal spike-train responses in the presence of threshold noise
title_full Neuronal spike-train responses in the presence of threshold noise
title_fullStr Neuronal spike-train responses in the presence of threshold noise
title_full_unstemmed Neuronal spike-train responses in the presence of threshold noise
title_short Neuronal spike-train responses in the presence of threshold noise
title_sort neuronal spike-train responses in the presence of threshold noise
topic Integrate-and-fire
Arnol'd tongues
Stochastic mode-locking
Threshold noise
First passage times
Neural coding
url https://eprints.nottingham.ac.uk/1333/
https://eprints.nottingham.ac.uk/1333/
https://eprints.nottingham.ac.uk/1333/