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Analytical modelling of temperature effects on an AMPA-type synapse

Overview of attention for article published in Journal of Computational Neuroscience, May 2018
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Title
Analytical modelling of temperature effects on an AMPA-type synapse
Published in
Journal of Computational Neuroscience, May 2018
DOI 10.1007/s10827-018-0684-x
Pubmed ID
Authors

Dominik S. Kufel, Grzegorz M. Wojcik

Abstract

It was previously reported, that temperature may significantly influence neural dynamics on the different levels of brain function. Thus, in computational neuroscience, it would be useful to make models scalable for a wide range of various brain temperatures. However, lack of experimental data and an absence of temperature-dependent analytical models of synaptic conductance does not allow to include temperature effects at the multi-neuron modeling level. In this paper, we propose a first step to deal with this problem: A new analytical model of AMPA-type synaptic conductance, which is able to incorporate temperature effects in low-frequency stimulations. It was constructed based on Markov model description of AMPA receptor kinetics using the set of coupled ODEs. The closed-form solution for the set of differential equations was found using uncoupling assumption (introduced in the paper) with few simplifications motivated both from experimental data and from Monte Carlo simulation of synaptic transmission. The model may be used for computationally efficient and biologically accurate implementation of temperature effects on AMPA receptor conductance in large-scale neural network simulations. As a result, it may open a wide range of new possibilities for researching the influence of temperature on certain aspects of brain functioning.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 29%
Student > Bachelor 2 14%
Professor 1 7%
Lecturer 1 7%
Student > Master 1 7%
Other 1 7%
Unknown 4 29%
Readers by discipline Count As %
Neuroscience 6 43%
Engineering 3 21%
Computer Science 1 7%
Unknown 4 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 May 2018.
All research outputs
#15,866,607
of 23,577,654 outputs
Outputs from Journal of Computational Neuroscience
#175
of 312 outputs
Outputs of similar age
#209,101
of 326,791 outputs
Outputs of similar age from Journal of Computational Neuroscience
#2
of 5 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 312 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 29th percentile – i.e., 29% of its peers scored the same or lower than it.
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