Levy noise-induced near-death spikes and phase transitions of a biological neural network

Near-death spikes or near-death surges are a sudden increase in neuron activity in the human brain before neurons end their firings. Just before a person is clinically dead, such spikes are observed in certain cases, so the name is near-death spikes. The reason for this behavior is the lack of oxygen in brain (Chawla et al. in J Palliat Med 12(12):1095-1100, 2009). In this study, it is demonstrated that a particular type of noise called Levy noise can generate such activity in the neural network of the worm Caenorhabditis elegans. The study identified different parameter regions of noise at which the network makes transitions from one synchronous state to another and the mechanism behind them. Such transitions are already reported in cortical regions of brain (Canavero et al. in Surg Neurol Int 7(Suppl 24):S623-S625, 2016). During the transition period between asynchronous and synchronous firing states, network is more susceptible to changes in firing pattern of individual neurons (Zandt et al. in PLoS ONE 6(7):e22127, 2011; Uzuntarla et al. Neural Netw 110:131-140, 2019). In this work, it is demonstrated that the recognized parameter regions can be used to control the network dynamics. The study also identified Levy noise values at which the network displays generation of waves of different frequencies. This result suggests a new method for neurostimulation in the case of traumatic brain injury. The study reveals that the characteristic exponent (alpha) of the noise has better influence on the network dynamics than the scale parameter of noise (D) and the synaptic coupling constant (Gsyn) of the network. The neuronal network even displayed Gamma oscillations for large values of alpha. If the parameters of the neurons are made chaotic, the network firing rate is diminished and it displayed Delta and Theta oscillations.