Scholarly article on topic 'A computational model of a strongly facilitating synapse'

A computational model of a strongly facilitating synapse Academic research paper on "Medical engineering"

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Academic research paper on topic "A computational model of a strongly facilitating synapse"

Jçdrzejewska-Szmek et al. BMC Neuroscience 2011, 12(Suppl 1):P159 http://www.biomedcentral.com/1471 -2202/12/S1/P159

Neuroscience

POSTER PRESENTATION Open Access

A computational model of a strongly facilitating synapse

Joanna Jçdrzejewska-Szmek1*, Jarostaw Zygierewicz1, Aleksander Michalski2

From Twentieth Annual Computational Neuroscience Meeting: CNS*2011 Stockholm, Sweden. 23-28 July 2011

We propose a new model of strongly facilitating synapse. It is described in terms of resources R which can be in two states: available and inactivated (recovery constant -tg). It assumes that for the release of neurotransmitter to the synaptic cleft a fraction (u) of available resources must bu used (as in [2]). This fraction is elevated by every AP (by a factor ~ u*U) and decays in

Table 1 Results of the models fit to the experimental data

parameter tf U tr

Value and 68% confidence range in 10± 2 ms 0.18 ± 0.07 130 ms

* Correspondence: asia@fuw.edu.pl

1BiomedicalPhysics, Faculty of Physics, University of Warsaw, ul.Hoza 69, 00681 Warszawa, Poland

Full list of author information is available at the end of the article

Bio Med Central

between APs (facilitation constant - tf). u related to the calcium concentration. It is further assumed that the activation of the neurotransmitter release machinery requires binding of 5 calcium ions to synaptotagmin[3], binding synaptic vesicles to the presynaptic membrane. Hence the postsynaptic current is proportional to u5*R*8(t-tAP).

The model allows to derive analytic formulas for the measures reported in the experimental literature, e.g. EPSP integrals [1] for consecutive action potentials arriving at the synapse. Those measures were used to estimate the model parameters so that it corresponds to the synapses reported in [1]. The obtained parameter values (Table 1) are in the physiologically plausible range. The best fit curve is presented in Fig. 1. The model allows to make predictions which can be used to validate it. In our case - the stationary current

© 2011 Jq^drzejewska-Szmek et al; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.Org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

[msj Frequency I

Figure 1 Best fit to the experimentalresults from [1] and stationary current predictions. Best-fit parameters can be found in Tab.

Jçdrzejewska-Szmek et al. BMC Neuroscience 2011, 12(Suppl 1):P159 Page 2 of 2

http://www.biomedcentral.com/1471 -2202/12/S1/P159

(normalized to the typical synaptic current) which can be seen in Fig. 1 - information coding is possible for physiological spike frequencies.

Author details

1BiomedicalPhysics, Faculty of Physics, University of Warsaw, ul.Hoza 69, 00681 Warszawa, Poland. 2Laboratory of Neurobiology of Development and Evolution, Nencki Institute of ExperimentalBiology, ul.L.Pasteura 3, 02-093 Warszawa, Poland.

Published: 18 July 2011

References

1. Thomson AM: Activity-dependent properties of synaptic transmission at two classes of connections made byrat neocortical pyramidal axons in vitro. J Physiol 1997, 502:131-147.

2. Markram H, Wang Y, Tsodyks M: Differential signaling via the same axon of neocortical pyramidal neurons. Proc Natl Acad Sci USA 1998, 95(9):5323-532.

3. Fuson KL, Montes M, Robert JJ, Sutton RB: Structure of human synaptotagmin 1 C2AB in the Absence of Ca2+ reveals a novel domain association. Biochemistry 2007, 46:13041-13048.

doi:10.1186/1471-2202-12-S1-P159

Cite this article as: Jçdrzejewska-Szmek et al.: A computational model of a strongly facilitating synapse. BMC Neuroscience 2011 12(Suppl 1):P159.

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