Eur. Phys. J. Special Topics 227, 1029–1038 (2018)
https://doi.org/10.1140/epjst/e2018-800036-5

Regular Article

Dynamics of map-based neuronal network with modified spike-timing-dependent plasticity

¹ REC “Artificial Intelligence Systems and Neurotechnology”, Yuri Gagarin State Technical University of Saratov, Politechnicheskaya Str. 77, Saratov 410054, Russia
² Center for Biomedical Technology, Technical University of Madrid, Campus Montegancedo, 28223 Pozuelo de Alarcon, Madrid, Spain

^a e-mail: hramovae@gmail.com

Received: 31 March 2018
Received in final form: 21 June 2018
Published online: 12 December 2018

Abstract

The effect of adaptive coupling is studied in a neural network of randomly-coupled Rulkov maps. As an adaptive mechanism, we propose a modified spike-timing-dependent plasticity (STDP) rule with implemented homeostatic property. The comparison of the results of classical and modified STDP shows that the implication of homeostatic property results in significant changes in the network dynamics. Moreover, the neural network with modified STPD demonstrates much more pronounced dynamical changes when internal noise and stimulus amplitudes are varied. The use of the modified rule also leads to decreasing coherence and characteristic correlation time in the system.