Temporal Coding Model of Spiking Output for Retinal Ganglion Cells

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Traditionally, it has been assumed that the important information from a visual scene is encoded within the average firing rate of a retinal ganglion cell. Many modelling techniques thus focus solely on estimating a firing rate rather than a cells temporal response. It has been argued however that the latter is more important, as intricate details of the visual scene are stored within the temporal nature of the code. In this paper, we present a model that accurately describes the input/output response of a retinal ganglion cell in terms of its temporal coding. The approach borrows a concept of layout from popular implementations, such as the linear-nonlinear Poisson method that produces an estimated spike rate prior to generating a spiking output. Using the well-known Izhikevich neuron as the spike generator and various approaches for spike rate estimation, we show that the resulting overall system predicts a retinal ganglion cells response to novel stimuli in terms of bursting and periods of silence with reasonable accuracy.
LanguageEnglish
Title of host publicationUnknown Host Publication
Number of pages7
Publication statusE-pub ahead of print - 20 Mar 2016
EventCOGNITIVE 2016 : The Eighth International Conference on Advanced Cognitive Technologies and Applications - Rome, Italy
Duration: 20 Mar 2016 → …

Conference

ConferenceCOGNITIVE 2016 : The Eighth International Conference on Advanced Cognitive Technologies and Applications
Period20/03/16 → …

Fingerprint

Neurons

Keywords

  • Spiking
  • Retinal Ganglion Cell
  • ANN
  • NARMAX

Cite this

@inproceedings{bb6f9d08963d499bbd89fe237ad10e9e,
title = "Temporal Coding Model of Spiking Output for Retinal Ganglion Cells",
abstract = "Traditionally, it has been assumed that the important information from a visual scene is encoded within the average firing rate of a retinal ganglion cell. Many modelling techniques thus focus solely on estimating a firing rate rather than a cells temporal response. It has been argued however that the latter is more important, as intricate details of the visual scene are stored within the temporal nature of the code. In this paper, we present a model that accurately describes the input/output response of a retinal ganglion cell in terms of its temporal coding. The approach borrows a concept of layout from popular implementations, such as the linear-nonlinear Poisson method that produces an estimated spike rate prior to generating a spiking output. Using the well-known Izhikevich neuron as the spike generator and various approaches for spike rate estimation, we show that the resulting overall system predicts a retinal ganglion cells response to novel stimuli in terms of bursting and periods of silence with reasonable accuracy.",
keywords = "Spiking, Retinal Ganglion Cell, ANN, NARMAX",
author = "Philip Vance and Gautham Das and Dermot Kerr and SA Coleman and Martin McGinnity",
year = "2016",
month = "3",
day = "20",
language = "English",
isbn = "978-1-61208-462-6",
booktitle = "Unknown Host Publication",

}

Vance, P, Das, G, Kerr, D, Coleman, SA & McGinnity, M 2016, Temporal Coding Model of Spiking Output for Retinal Ganglion Cells. in Unknown Host Publication. COGNITIVE 2016 : The Eighth International Conference on Advanced Cognitive Technologies and Applications, 20/03/16.

Temporal Coding Model of Spiking Output for Retinal Ganglion Cells. / Vance, Philip; Das, Gautham; Kerr, Dermot; Coleman, SA; McGinnity, Martin.

Unknown Host Publication. 2016.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Temporal Coding Model of Spiking Output for Retinal Ganglion Cells

AU - Vance, Philip

AU - Das, Gautham

AU - Kerr, Dermot

AU - Coleman, SA

AU - McGinnity, Martin

PY - 2016/3/20

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N2 - Traditionally, it has been assumed that the important information from a visual scene is encoded within the average firing rate of a retinal ganglion cell. Many modelling techniques thus focus solely on estimating a firing rate rather than a cells temporal response. It has been argued however that the latter is more important, as intricate details of the visual scene are stored within the temporal nature of the code. In this paper, we present a model that accurately describes the input/output response of a retinal ganglion cell in terms of its temporal coding. The approach borrows a concept of layout from popular implementations, such as the linear-nonlinear Poisson method that produces an estimated spike rate prior to generating a spiking output. Using the well-known Izhikevich neuron as the spike generator and various approaches for spike rate estimation, we show that the resulting overall system predicts a retinal ganglion cells response to novel stimuli in terms of bursting and periods of silence with reasonable accuracy.

AB - Traditionally, it has been assumed that the important information from a visual scene is encoded within the average firing rate of a retinal ganglion cell. Many modelling techniques thus focus solely on estimating a firing rate rather than a cells temporal response. It has been argued however that the latter is more important, as intricate details of the visual scene are stored within the temporal nature of the code. In this paper, we present a model that accurately describes the input/output response of a retinal ganglion cell in terms of its temporal coding. The approach borrows a concept of layout from popular implementations, such as the linear-nonlinear Poisson method that produces an estimated spike rate prior to generating a spiking output. Using the well-known Izhikevich neuron as the spike generator and various approaches for spike rate estimation, we show that the resulting overall system predicts a retinal ganglion cells response to novel stimuli in terms of bursting and periods of silence with reasonable accuracy.

KW - Spiking

KW - Retinal Ganglion Cell

KW - ANN

KW - NARMAX

M3 - Conference contribution

SN - 978-1-61208-462-6

BT - Unknown Host Publication

ER -