Chimera states in Leaky Integrate-and-Fire dynamics with power law coupling

2020 ◽  
Vol 93 (8) ◽  
Author(s):  
Astero Provata ◽  
Ioannis E. Venetis
Author(s):  
Jorgen Vitting Andersen ◽  
Naji Masaad

We introduce tools to capture the dynamics of three different pathways, in which the synchronization of human decision making could lead to turbulent periods and contagion phenomena in financial markets. The first pathway is caused when stock market indices, seen as a set of coupled integrate-and-fire oscillators, synchronize in frequency. The integrate-and-fire dynamics happens due to "change blindness", a trait in human decision making where people have the tendency to ignore small changes, but take action when a large change happens. The second pathway happens due to feedback mechanisms between market performance and the use of certain (decoupled) trading strategies. The third pathway occurs through the effects of communication and its impact on human decision making. A model is introduced in which financial market performance has an impact on decision making through communication between people. Conversely, the sentiment created via communication has an impact on financial market performance.


2012 ◽  
Vol 22 (07) ◽  
pp. 1250174 ◽  
Author(s):  
CESAR H. COMIN ◽  
JOÃO L. B. BATISTA ◽  
MATHEUS P. VIANA ◽  
LUCIANO DA F. COSTA ◽  
BRUNO A. N. TRAVENÇOLO ◽  
...  

The transient and equilibrium properties of dynamics unfolding in complex systems can depend critically on specific topological features of the underlying interconnections. In this work, we investigate such a relationship with respect to the integrate-and-fire dynamics emanating from a source node and an extended network model that allows control of the small-world feature as well as the length of the long-range connections. A systematic approach to investigate the local and global correlations between structural and dynamical features of the networks was adopted that involved extensive simulations (one and a half million cases) so as to obtain two-dimensional correlation maps. Smooth, but diverse surfaces of correlation values were obtained in all cases. Regarding the global cases, it has been verified that the onset avalanche time (but not its intensity) can be accurately predicted from the structural features within specific regions of the map (i.e. networks with specific structural properties). The analysis at local level revealed that the dynamical features before the avalanches can also be accurately predicted from structural features. This is not possible for the dynamical features after the avalanches take place. This is so because the overall topology of the network predominates over the local topology around the source at the stationary state.


Author(s):  
Anirban Nandi ◽  
Heinz Schättler ◽  
Jason T. Ritt ◽  
ShiNung Ching

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256034
Author(s):  
Kyra L. Kadhim ◽  
Ann M. Hermundstad ◽  
Kevin S. Brown

Identifying coordinated activity within complex systems is essential to linking their structure and function. We study collective activity in networks of pulse-coupled oscillators that have variable network connectivity and integrate-and-fire dynamics. Starting from random initial conditions, we see the emergence of three broad classes of behaviors that differ in their collective spiking statistics. In the first class (“temporally-irregular”), all nodes have variable inter-spike intervals, and the resulting firing patterns are irregular. In the second (“temporally-regular”), the network generates a coherent, repeating pattern of activity in which all nodes fire with the same constant inter-spike interval. In the third (“chimeric”), subgroups of coherently-firing nodes coexist with temporally-irregular nodes. Chimera states have previously been observed in networks of oscillators; here, we find that the notions of temporally-regular and chimeric states encompass a much richer set of dynamical patterns than has yet been described. We also find that degree heterogeneity and connection density have a strong effect on the resulting state: in binomial random networks, high degree variance and intermediate connection density tend to produce temporally-irregular dynamics, while low degree variance and high connection density tend to produce temporally-regular dynamics. Chimera states arise with more frequency in networks with intermediate degree variance and either high or low connection densities. Finally, we demonstrate that a normalized compression distance, computed via the Lempel-Ziv complexity of nodal spike trains, can be used to distinguish these three classes of behavior even when the phase relationship between nodes is arbitrary.


2019 ◽  
Vol 29 (4) ◽  
pp. 043106 ◽  
Author(s):  
Moises S. Santos ◽  
Paulo R. Protachevicz ◽  
Kelly C. Iarosz ◽  
Iberê L. Caldas ◽  
Ricardo L. Viana ◽  
...  

2015 ◽  
Vol 66 ◽  
pp. 13-22 ◽  
Author(s):  
N.D. Tsigkri-DeSmedt ◽  
J. Hizanidis ◽  
P. Hövel ◽  
A. Provata

Sign in / Sign up

Export Citation Format

Share Document