Figure 1.
Stability region of three delay-coupled networks with different nodes
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doi: 10.3934/era.2021022
Complexity in time-delay networks of multiple interacting neural groups
Department of Engineering Mechanics, College of Mechanics and Materials, Hohai University, Nanjing 211100, China |
Coupled networks are common in diverse real-world systems and the dynamical properties are crucial for their function and application. This paper focuses on the behaviors of a network consisting of mutually coupled neural groups and time-delayed interactions. These interacting groups can include different sets of nodes and topological architecture, respectively. The local and global stability of the system are analyzed and the stable regions and bifurcation curves in parameter planes are obtained. Different patterns of bifurcated solutions arising from trivial and non-trivial equilibrium points are given, such as the coexistence of non-trivial equilibrium points and periodic responses and multiple coexisting periodic orbits. The bifurcation diagrams are shown and plenty of complex dynamic phenomena are observed, such as multi-period oscillations and multiple coexisting attractors.
Mathematics Subject Classification:
70K50, 92B20, 34Kxx.
Citation:
Xiaochen Mao, Weijie Ding, Xiangyu Zhou, Song Wang, Xingyong Li.
Complexity in time-delay networks of multiple interacting neural groups. Electronic Research Archive, doi: 10.3934/era.2021022
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S. Majhi, M. Perc and D. Ghosh, Chimera states in uncoupled neurons induced by a multilayer structure, Sci. Rep., 6 (2016), 39033. Google Scholar |
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X. Mao, X. Li, W. Ding, S. Wang, X. Zhou and L. Qiao, Dynamics of a multiplex neural network with delayed couplings, Appl. Math. Mech. (Eng. Edit.), (2021).
doi: 10.1007/s10483-021-2709-6. |
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D. Nikitin, I. Omelchenko, A. Zakharova, M. Avetyan, A. L. Fradkov and E. Schöll, Complex partial synchronization patterns in networks of delay-coupled neurons, Philos. Trans. Roy. Soc. A, 377 (2019), 20180128, 19 pp.
doi: 10.1098/rsta.2018.0128. |
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J. Sawicki, I. Omelchenko, A. Zakharova and E. Schoell, Delay controls chimera relay synchronization in multiplex networks, Phys. Rev. E, 98 (2018), 062224. Google Scholar |
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Z. Wang, S. Liang, C. A. Molnar, T. Insperger and G. Stepan, Parametric continuation algorithm for time-delay systems and bifurcation caused by multiple characteristic roots, Nonlinear Dynam., (2020).
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X. Xu, D. Yu and Z. Wang,
Inter-layer synchronization of periodic solutions in two coupled rings with time delay, Physica D, 396 (2019), 1-11.
doi: 10.1016/j.physd.2019.02.010. |
show all references
References:
| [1] |
F. Battiston, V. Nicosia, M. Chavez and V. Latora, Multilayer motif analysis of brain networks, Chaos, 27 (2017), 047404, 8 pp.
doi: 10.1063/1.4979282. |
| [2] |
S. Boccaletti, G. Bianconi, R. Criado, C. I. del Genio, J. Gómez-Gardeñes, M. Romance, I. Sendiña-Nadal, Z. Wang and M. Zanin,
The structure and dynamics of multilayer networks, Phys. Rep., 544 (2014), 1-122.
doi: 10.1016/j.physrep.2014.07.001. |
| [3] |
S. A. Campbell, R. Edwards and P. van den Driessche,
Delayed coupling between two neural network loops, SIAM J. Appl. Math., 65 (2004), 316-335.
doi: 10.1137/S0036139903434833. |
| [4] |
D. G. Fan, Y. H. Zheng, Z. C. Yang and Q. Y. Wang, Improving control effects of absence seizures using single-pulse alternately resetting stimulation (SARS) of corticothalamic circuit, Appl. Math. Mech. (Eng. Edit.), 41 (2020), 1287-1302. Google Scholar |
| [5] |
F. Frohlich and M. Bazhenov, Coexistence of tonic firing and bursting in cortical neurons, Phys. Rev. E, 74 (2006), 031922. Google Scholar |
| [6] |
F. Han, Z. Wang, Y. Du, X. Sun and B. Zhang, Robust synchronization of bursting Hodgkin-Huxley neuronal systems coupled by delayed chemical synapses, Int. J. Nonlinear Mech., 70 (2015), 105-111. Google Scholar |
| [7] |
J. J. Hopfield, Neurons with graded response have collective computational properties like those of two-state neurons, Proc. Nati. Acad. Sci. USA, 81 (1984), 3088-3092. Google Scholar |
| [8] |
C.-H. Hsu and T.-S. Yang,
Periodic oscillations arising and death in delay-coupled neural loops, Internat. J. Bifur. Chaos Appl. Sci. Engrg., 17 (2007), 4015-4032.
doi: 10.1142/S0218127407019834. |
| [9] |
H. Y. Hu and Z. H. Wang, Dynamics of Controlled Mechanical Systems with Delayed Feedback, Springer-Verlag, Heidelberg, 2002.
doi: 10.1007/978-3-662-05030-9. |
| [10] |
S. Majhi, M. Perc and D. Ghosh, Chimera states in uncoupled neurons induced by a multilayer structure, Sci. Rep., 6 (2016), 39033. Google Scholar |
| [11] |
X. Mao, X. Li, W. Ding, S. Wang, X. Zhou and L. Qiao, Dynamics of a multiplex neural network with delayed couplings, Appl. Math. Mech. (Eng. Edit.), (2021).
doi: 10.1007/s10483-021-2709-6. |
| [12] |
D. Nikitin, I. Omelchenko, A. Zakharova, M. Avetyan, A. L. Fradkov and E. Schöll, Complex partial synchronization patterns in networks of delay-coupled neurons, Philos. Trans. Roy. Soc. A, 377 (2019), 20180128, 19 pp.
doi: 10.1098/rsta.2018.0128. |
| [13] |
J. Sawicki, I. Omelchenko, A. Zakharova and E. Schoell, Delay controls chimera relay synchronization in multiplex networks, Phys. Rev. E, 98 (2018), 062224. Google Scholar |
| [14] |
Z. Wang, S. Liang, C. A. Molnar, T. Insperger and G. Stepan, Parametric continuation algorithm for time-delay systems and bifurcation caused by multiple characteristic roots, Nonlinear Dynam., (2020).
doi: 10.1007/s11071-020-05799-w. |
| [15] |
X. Xu, D. Yu and Z. Wang,
Inter-layer synchronization of periodic solutions in two coupled rings with time delay, Physica D, 396 (2019), 1-11.
doi: 10.1016/j.physd.2019.02.010. |
Figure 2.
Stability region of four delay-coupled networks, where the solid curves are $ 1-\alpha-2\alpha^2-\beta_1+\alpha\beta_1 = 0 $ and $ 1-\alpha-2\alpha^2+\beta_1-\alpha\beta_1 = 0 $
Figure 3.
Amplitudes of the periodic oscillations when the sum of coupling time delays varies. (a) $ c_1 = -1.4 $ , $ c_2 = 0.4 $ , $ c_3 = 2.5 $ , $ \tau_1 = 0.3 $ , and $ \tau_2 = 0.5 $ ; (b) $ c_1 = 1.5 $ , $ c_2 = 0.8 $ , $ c_3 = 1.4 $ , $ \tau_1 = 0.1 $ , and $ \tau_2 = 0.1 $
Figure 4.
Stability region of the trivial equilibrium of three coupled networks with different topologies. (a) $ a = 0.4 $ ; (b) $ c = -1.3 $
Figure 5.
Responses of interacting three-node networks with different topologies. (a) $ \tau_s = 1.5 $ ; (b) $ \tau_s = 1.7 $ ; (c) $ \tau_s = 2.1 $
Figure 6.
Phase trajectories of the network when $ \tau_s = 0.17 $ . (a) Two coexisting period-6 oscillations under initial conditions IC1 (0.1, 0.2, 0.5, 0.8, 0.3, 0.7, 0.9, 0.4, 0.6) and IC2 (-0.1, -0.2, -0.5, -0.8, -0.3, -0.7, -0.9, -0.4, -0.6), respectively; (b) Two chaotic motions under initial conditions IC3 (-0.1, 0.2, 0.5, 0.8, 0.3, 0.7, -0.9, 0.4, 0.6) and IC4 (0.1, -0.2, -0.5, -0.8, -0.3, -0.7, 0.9, -0.4, -0.6), respectively. The blue, red, green, and purple curves represent phase trajectories under initial conditions IC1, IC2, IC3, and IC4, respectively
Figure 7.
Phase trajectories of the network when $ \tau_s = 0.25 $ . (a) Two period-3 oscillations under initial conditions IC1 and IC2, respectively; (b) Two chaotic motions under initial conditions IC3 and IC4, respectively
Figure 8.
Phase trajectories of the network when $ \tau_s = 0.43 $ . (a) Two separated chaotic attractors under initial conditions IC1 and IC2, respectively; (b) Two coexisting period-4 orbits under initial conditions IC3 and IC4, respectively
Figure 9.
Phase trajectories of the network when $ \tau_s = 0.47 $ . (a) Two chaotic responses under initial conditions IC1 and IC2, respectively; (b) Two symmetric period-2 oscillations under initial conditions IC3 and IC4, respectively
Figure 10.
Phase trajectories of the network when $ \tau_s = 1.73 $ . (a) A pair of period-4 responses under initial conditions IC1 and IC2, respectively; (b) Another pair of period-4 oscillations under initial conditions IC3 and IC4, respectively
Figure 11.
Bifurcation diagrams on the Poincaré section when the time delay varies. The blue, red, green, and purple dots are obtained under the initial conditions IC1, IC2, IC3, and IC4, respectively
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