Symbolic analysis of bursting dynamical regimes of Rulkov neural networks

被引:11
作者
Budzinski, R. C. [1 ]
Lopes, S. R. [1 ]
Masoller, C. [2 ]
机构
[1] Univ Fed Parana, Dept Phys, BR-81531980 Curitiba, Parana, Brazil
[2] Univ Politecn Cataluna, Dept Phys, Rambla St,Nebridi 22, Barcelona 08222, Spain
关键词
Neural networks; Neural encode information; Ordinal symbolic analysis; PERMUTATION ENTROPY; STATISTICS; SYNCHRONIZATION; SIGNAL;
D O I
10.1016/j.neucom.2020.05.122
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Neurons modeled by the Rulkov map display a variety of dynamic regimes that include tonic spikes and chaotic bursting. Here we study an ensemble of bursting neurons coupled with the Watts-Strogatz small world topology. We characterize the sequences of bursts using the symbolic method of time-series analysis known as ordinal analysis, which detects nonlinear temporal correlations. We show that the probabilities of the different symbols distinguish different dynamical regimes, which depend on the coupling strength and the network topology. These regimes have different spatio-temporal properties that can be visualized with raster plots.& nbsp; (C)& nbsp;2021 Elsevier B.V. All rights reserved.
引用
收藏
页码:44 / 51
页数:8
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