Markovian noise-induced delta synchronization approach for Hindmarsh-Rose model

The paper explores noise-induced synchronization in uncoupled Hindmarsh-Rose neurons, introducing two distinctive elements: the application of Markovian noise and an analysis of synchronization via unpredictability. The noise is defined as an unpredictable and continuous process with characteristics proper for stochasticity. While identical synchronization is also investigated, the primary focus is to reveal synchronization in noise intensity domains that elude conventional detection methods, through delta synchronization within the neural system. Furthermore, a stronger form of synchronization, namely complete synchronization of unpredictability, is found to emerge in the domain with identical synchronization. The research findings are substantiated by numerical outcomes assessing unpredictability and synchronization, alongside comprehensive tables displaying characteristic time sequences for synchronization.