Advanced

Multicompartment simulations of NMDA receptor based facilitation in an insect target tracking neuron

Bekkouche, Bo LU ; Shoemaker, Patrick A.; Fabian, Joseph LU ; Rigosi, Elisa LU ; Wiederman, Steven D. and O’Carroll, David C. LU (2017) 26th International Conference on Artificial Neural Networks, ICANN 2017 In Artificial Neural Networks and Machine Learning – ICANN 2017 - 26th International Conference on Artificial Neural Networks, Proceedings 10613 LNCS. p.397-404
Abstract

Computational modelling of neurons on different scales provides not only methods to explore mechanisms observed in vivo but also for testing hypotheses that would be impossible physiologically. In this paper we present initial computational analysis of insect lobula small target motion detector (STMD) neurons. We simulate a multicompartment model in combination with a bioinspired model for front-end processing. This combination of different simulation environments enables a combination of scale and detail not possible otherwise. The addressed hypothesis is that facilitation involves N-methyl-D-aspartate (NMDA) synapses which map retinotopically onto the dendritic tree of the STMD neuron. Our results show that a stronger response... (More)

Computational modelling of neurons on different scales provides not only methods to explore mechanisms observed in vivo but also for testing hypotheses that would be impossible physiologically. In this paper we present initial computational analysis of insect lobula small target motion detector (STMD) neurons. We simulate a multicompartment model in combination with a bioinspired model for front-end processing. This combination of different simulation environments enables a combination of scale and detail not possible otherwise. The addressed hypothesis is that facilitation involves N-methyl-D-aspartate (NMDA) synapses which map retinotopically onto the dendritic tree of the STMD neuron. Our results show that a stronger response (facilitation) is generated when using continuous visual stimuli as opposed to random jumps. We observe two levels of facilitation which may be involved in selective attention.

(Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Bioinspired, Computational neuroscience, Facilitation, Model, Multicompartment, Selective attention, Simulation, Small target motion detection
in
Artificial Neural Networks and Machine Learning – ICANN 2017 - 26th International Conference on Artificial Neural Networks, Proceedings
volume
10613 LNCS
pages
8 pages
publisher
Springer Verlag
conference name
26th International Conference on Artificial Neural Networks, ICANN 2017
external identifiers
  • scopus:85034272706
ISSN
1611-3349
0302-9743
ISBN
9783319685991
DOI
10.1007/978-3-319-68600-4_46
language
English
LU publication?
yes
id
9f12266b-b9cf-4ca6-ac0d-b5eae92f6485
date added to LUP
2017-12-11 12:03:19
date last changed
2018-05-29 11:24:57
@inproceedings{9f12266b-b9cf-4ca6-ac0d-b5eae92f6485,
  abstract     = {<p>Computational modelling of neurons on different scales provides not only methods to explore mechanisms observed in vivo but also for testing hypotheses that would be impossible physiologically. In this paper we present initial computational analysis of insect lobula small target motion detector (STMD) neurons. We simulate a multicompartment model in combination with a bioinspired model for front-end processing. This combination of different simulation environments enables a combination of scale and detail not possible otherwise. The addressed hypothesis is that facilitation involves N-methyl-D-aspartate (NMDA) synapses which map retinotopically onto the dendritic tree of the STMD neuron. Our results show that a stronger response (facilitation) is generated when using continuous visual stimuli as opposed to random jumps. We observe two levels of facilitation which may be involved in selective attention.</p>},
  author       = {Bekkouche, Bo and Shoemaker, Patrick A. and Fabian, Joseph and Rigosi, Elisa and Wiederman, Steven D. and O’Carroll, David C.},
  booktitle    = {Artificial Neural Networks and Machine Learning – ICANN 2017 - 26th International Conference on Artificial Neural Networks, Proceedings},
  isbn         = {9783319685991},
  issn         = {1611-3349},
  keyword      = {Bioinspired,Computational neuroscience,Facilitation,Model,Multicompartment,Selective attention,Simulation,Small target motion detection},
  language     = {eng},
  pages        = {397--404},
  publisher    = {Springer Verlag},
  title        = {Multicompartment simulations of NMDA receptor based facilitation in an insect target tracking neuron},
  url          = {http://dx.doi.org/10.1007/978-3-319-68600-4_46},
  volume       = {10613 LNCS},
  year         = {2017},
}