Geodesic
Simulation of spontaneous activity in neuronal cultures with long-term plasticity
Matematičeskaâ biologiâ i bioinformatika, Tome 10 (2015) no. 1, pp. 234-244.

Voir la notice de l'article provenant de la source Math-Net.Ru

Existence of spontaneous population bursts is a widely studied phenomenon observed in neuronal cultures in vitro. Recent models of neuronal cultures network activity consist of a number of burst generating mechanisms such as synaptic noise and presence of pacemaker neurons in the network. In the previous simulations of bursting in neuronal cultures synaptic weights change in accordance with the rule of short-term plasticity whereas the long-term values of them, and hence the network structure, remain unchanged. In this paper we reproduce neuronal network models with static synapses, and then investigate spontaneous activity changes in neuronal networks with long-term plasticity defined by STDP rule. Our results demonstrate that introduction of long-term plasticity in the model leads to discrepancy with the experimental data. 
@article{MBB_2015_10_1_a15,
     author = {A. A. Degterev and M. S. Burtsev},
     title = {Simulation of spontaneous activity in neuronal cultures with long-term plasticity},
     journal = {Matemati\v{c}eska\^a biologi\^a i bioinformatika},
     pages = {234--244},
     publisher = {mathdoc},
     volume = {10},
     number = {1},
     year = {2015},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/MBB_2015_10_1_a15/}
}
TY  - JOUR
AU  - A. A. Degterev
AU  - M. S. Burtsev
TI  - Simulation of spontaneous activity in neuronal cultures with long-term plasticity
JO  - Matematičeskaâ biologiâ i bioinformatika
PY  - 2015
SP  - 234
EP  - 244
VL  - 10
IS  - 1
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/MBB_2015_10_1_a15/
LA  - ru
ID  - MBB_2015_10_1_a15
ER  - 
%0 Journal Article
%A A. A. Degterev
%A M. S. Burtsev
%T Simulation of spontaneous activity in neuronal cultures with long-term plasticity
%J Matematičeskaâ biologiâ i bioinformatika
%D 2015
%P 234-244
%V 10
%N 1
%I mathdoc
%U http://geodesic.mathdoc.fr/item/MBB_2015_10_1_a15/
%G ru
%F MBB_2015_10_1_a15
A. A. Degterev; M. S. Burtsev. Simulation of spontaneous activity in neuronal cultures with long-term plasticity. Matematičeskaâ biologiâ i bioinformatika, Tome 10 (2015) no. 1, pp. 234-244. http://geodesic.mathdoc.fr/item/MBB_2015_10_1_a15/

[1] Wagenaar D. A., Pine J., Potter S. M., “An extremely rich repertoire of bursting patterns during the development of cortical cultures”, BMC Neurosci., 7:1 (2006), 11 | DOI

[2] Raichman N., Ben-Jacob E., “Identifying repeating motifs in the activation of synchronized bursts in cultured neuronal networks”, J. Neurosci. Methods, 170:1 (2008), 96–110 | DOI

[3] Pimashkin A., Kastalskiy I., Simonov A., Koryagina E., Mukhina I., Kazantsev V., “Spiking signatures of spontaneous activity bursts in hippocampal cultures”, Front. Comput. Neurosci., 5 (2011), 46 | DOI

[4] Lebedev R. D., Burtsev M. S., “Klasterizatsiya pachek spontannoi aktivnosti neironalnoi kultury”, XII Vserossiiskaya nauchno-tekhnicheskaya konferentsiya “Neiroinformatika-2010”, Sbornik nauchnykh trudov, v. 2, NIYaU MIFI, M., 2010, 296–303 | MR

[5] Shahaf G., Eytan D., Gal A., Kermany E., Lyakhov V., Zrenner C., Marom S., “Orderbased representation in random networks of cortical neurons”, PLoS Comput. Biol., 4:11 (2008) | DOI | MR

[6] Kermany E., Gal A., Lyakhov V., Meir R., Marom S., Eytan D., “Tradeoffs and constraints on neural representation in networks of cortical neurons”, J. Neurosci., 30:28 (2010), 9588–9596 | DOI

[7] Xydas D., Downes J. H., Spencer M. C., Hammond M. W., Nasuto S. J., Whalley B. J., Becerra V. M., Warwick K., “Revealing ensemble state transition patterns in multielectrode neuronal recordings using hidden Markov models”, IEEE Trans. Neural Syst. Rehabil. Eng., 19:4 (2011), 345–355 | DOI

[8] Gritsun T. A., Le Feber J., Stegenga J., Rutten W. L. C., “Network bursts in cortical cultures are best simulated using pacemaker neurons and adaptive synapses”, Biol. Cybern., 102 (2010), 293–310 | DOI | MR

[9] Gritsun T., le Feber J., Stegenga J., Rutten W. L. C., “Experimental analysis and computational modeling of interburst intervals in spontaneous activity of cortical neuronal culture”, Biol. Cybern., 105:3 (2011), 197–210 | DOI

[10] Gewaltig M. O., Diesmann M., “NEST (NEural Simulation Tool)”, Scholarpedia, 2:4 (2007), 1430 (data obrascheniya: 14.05.2015) http://www.scholarpedia.org/article/NEST_(NEural_ Simulation_Tool) | DOI

[11] Izhikevich E. M., “Simple model of spiking neurons”, IEEE Transactions on neural networks, 14:6 (2003), 1569–1572 | DOI | MR

[12] Orlandi J. G., Soriano J., Alvarez-Lacalle E., Teller S., Casademunt J., “Noise focusing and the emergence of coherent activity in neuronal cultures”, Nat. Phys., 9:9 (2013), 582–590 | DOI

[13] Markram H., Lubke J., Frotscher M., Sakmann B., “Regulation of synaptic efficacy by coincidence of postsynaptic APs and EPSPs”, Science, 275:5297 (1997), 213–215 | DOI

[14] Bi G., Poo M., “Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type”, J. Neurosci., 18:24 (1998), 10464–10472

[15] Song S., Miller K. D., Abbott L. F., “Competitive Hebbian learning through spike-timingdependent synaptic plasticity”, Nature Neuroscience, 3:9 (2000), 919–926 | DOI

[16] Gutig R., Aharonov R., Rotter S., Sompolinsky H., “Learning input correlations through nonlinear temporally asymmetric Hebbian plasticity”, J. Neurosci., 23:9 (2003), 3697–3714

[17] Chao Z. C., Bakkum D. J., Potter S. M., “Shaping embodied neural networks for adaptive goal-directed behavior”, PLoS Computational Biology, 4:3 (2008) | DOI | MR