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1. | Manchanda, K; Bose, A; Ramaswamy, R Collective dynamics in heterogeneous networks of neuronal cellular automata Journal Article Physica A: Statistical Mechanics and its Applications, 487 , pp. 111, 2017, ISSN: 0378-4371. Abstract | Links | BibTeX | Tags: Binary Mixtures, Cellular automata, Discrete Dynamics, Lyapunov exponent, Network Motif @article{Manchanda2017, title = {Collective dynamics in heterogeneous networks of neuronal cellular automata}, author = {K Manchanda and A Bose and R Ramaswamy}, url = {https://ramramaswamy.org/papers/167.pdf}, doi = {10.1016/j.physa.2017.06.021}, issn = {0378-4371}, year = {2017}, date = {2017-01-01}, journal = {Physica A: Statistical Mechanics and its Applications}, volume = {487}, pages = {111}, publisher = {Elsevier B.V.}, abstract = {We examine the collective dynamics of heterogeneous random networks of model neuronal cellular automata. Each automaton has b active states, a single silent state and r‚àíb‚àí1 refractory states, and can show ‚Äòspiking’ or ‚Äòbursting’ behavior, depending on the values of b. We show that phase transitions that occur in the dynamical activity can be related to phase transitions in the structure of Erdõs‚ÄìRényi graphs as a function of edge probability. Different forms of heterogeneity allow distinct structural phase transitions to become relevant. We also show that the dynamics on the network can be described by a semi-annealed process and, as a result, can be related to the Boolean Lyapunov exponent.}, keywords = {Binary Mixtures, Cellular automata, Discrete Dynamics, Lyapunov exponent, Network Motif}, pubstate = {published}, tppubtype = {article} } We examine the collective dynamics of heterogeneous random networks of model neuronal cellular automata. Each automaton has b active states, a single silent state and r‚àíb‚àí1 refractory states, and can show ‚Äòspiking’ or ‚Äòbursting’ behavior, depending on the values of b. We show that phase transitions that occur in the dynamical activity can be related to phase transitions in the structure of Erdõs‚ÄìRényi graphs as a function of edge probability. Different forms of heterogeneity allow distinct structural phase transitions to become relevant. We also show that the dynamics on the network can be described by a semi-annealed process and, as a result, can be related to the Boolean Lyapunov exponent. |