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Computationally efficient simulation of extracellular recordings with multielectrode arrays

Thorbergsson, Palmi Thor LU ; Garwicz, Martin LU ; Schouenborg, Jens LU and Johansson, Anders J LU (2012) In Journal of Neuroscience Methods 211(1). p.133-144
Abstract
In this paper we present a novel, computationally and memory efficient way of modeling the spatial dependency of measured spike waveforms in extracellular recordings of neuronal activity. We use compartment models to simulate action potentials in neurons and then apply linear source approximation to calculate the resulting extracellular spike waveform on a three dimensional grid of measurement points surrounding the neurons. We then apply traditional compression techniques and polynomial fitting to obtain a compact mathematical description of the spatial dependency of the spike waveform. We show how the compressed models can be used to efficiently calculate the spike waveform from a neuron in a large set of measurement points... (More)
In this paper we present a novel, computationally and memory efficient way of modeling the spatial dependency of measured spike waveforms in extracellular recordings of neuronal activity. We use compartment models to simulate action potentials in neurons and then apply linear source approximation to calculate the resulting extracellular spike waveform on a three dimensional grid of measurement points surrounding the neurons. We then apply traditional compression techniques and polynomial fitting to obtain a compact mathematical description of the spatial dependency of the spike waveform. We show how the compressed models can be used to efficiently calculate the spike waveform from a neuron in a large set of measurement points simultaneously and how the same procedure can be inversed to calculate the spike waveforms from a large set of neurons at a single electrode position. The compressed models have been implemented into an object oriented simulation tool that allows the simulation of multielectrode recordings that capture the variations in spike waveforms that are expected to arise between the different recording channels. The computational simplicity of our approach allows the simulation of a multi-channel recording of signals from large populations of neurons while simulating the activity of every neuron with a high level of detail. We have validated our compressed models against the original data obtained from the compartment models and we have shown, by example, how the simulation approach presented here can be used to quantify the performance in spike sorting as a function of electrode position. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Extracellular recordings, Multielectrode arrays, Electrode movements simulation, NEURON, Spike sorting, Spike detection
in
Journal of Neuroscience Methods
volume
211
issue
1
pages
133 - 144
publisher
Elsevier
external identifiers
  • wos:000311018900017
  • scopus:84866154020
ISSN
1872-678X
DOI
10.1016/j.jneumeth.2012.08.011
language
English
LU publication?
yes
id
166385ff-30f7-45a3-9661-1d5fbd0325d1 (old id 3122833)
alternative location
http://www.ncbi.nlm.nih.gov/pubmed/22960053?dopt=Abstract
date added to LUP
2012-09-28 11:13:48
date last changed
2017-03-12 03:06:26
@article{166385ff-30f7-45a3-9661-1d5fbd0325d1,
  abstract     = {In this paper we present a novel, computationally and memory efficient way of modeling the spatial dependency of measured spike waveforms in extracellular recordings of neuronal activity. We use compartment models to simulate action potentials in neurons and then apply linear source approximation to calculate the resulting extracellular spike waveform on a three dimensional grid of measurement points surrounding the neurons. We then apply traditional compression techniques and polynomial fitting to obtain a compact mathematical description of the spatial dependency of the spike waveform. We show how the compressed models can be used to efficiently calculate the spike waveform from a neuron in a large set of measurement points simultaneously and how the same procedure can be inversed to calculate the spike waveforms from a large set of neurons at a single electrode position. The compressed models have been implemented into an object oriented simulation tool that allows the simulation of multielectrode recordings that capture the variations in spike waveforms that are expected to arise between the different recording channels. The computational simplicity of our approach allows the simulation of a multi-channel recording of signals from large populations of neurons while simulating the activity of every neuron with a high level of detail. We have validated our compressed models against the original data obtained from the compartment models and we have shown, by example, how the simulation approach presented here can be used to quantify the performance in spike sorting as a function of electrode position.},
  author       = {Thorbergsson, Palmi Thor and Garwicz, Martin and Schouenborg, Jens and Johansson, Anders J},
  issn         = {1872-678X},
  keyword      = {Extracellular recordings,Multielectrode arrays,Electrode movements simulation,NEURON,Spike sorting,Spike detection},
  language     = {eng},
  number       = {1},
  pages        = {133--144},
  publisher    = {Elsevier},
  series       = {Journal of Neuroscience Methods},
  title        = {Computationally efficient simulation of extracellular recordings with multielectrode arrays},
  url          = {http://dx.doi.org/10.1016/j.jneumeth.2012.08.011},
  volume       = {211},
  year         = {2012},
}