  We perform a numerical study on the application of electromagnetic flux on a
heterogeneous network of Chialvo neurons represented by a ring-star topology.
Heterogeneities are realized by introducing additive noise modulations on both
the central-peripheral and the peripheral-peripheral coupling links in the
topology that not only vary in space but also in time. The variation in time is
understood by two coupling probabilities, one for the central-peripheral
connections and the other for the peripheral-peripheral connections
respectively, that updates the network topology with each iteration in time. We
have further reported the rich spatiotemporal patterns like two-cluster states,
chimera states, traveling waves, coherent, and asynchronized states that arise
throughout the network dynamics. We have also investigated the appearance of a
special kind of asynchronization behavior called "solitary nodes" that have
wide range of applications pertaining to real-world nervous systems. In order
to characterize the behavior of the nodes under the influence of these
heterogeneities, we have studied two different metrics called the
"cross-correlation coefficient" and the "synchronization error". Additionally,
to capture the statistical property of the network, for example, how complex
the system behaves, we have also studied a measure called "sample entropy".
Various two-dimensional color-coded plots are presented in the study to exhibit
how these metrics/measures behave with the variation of parameters. Finally,
how the nodes synchronize or asynchronize is shown via one-dimensional
bifurcation diagrams of the last instance of the main dynamical variable, i.e.,
the state variable associated with the membrane potential, against different
network parameters.
