The Role of hubs and Authorities Nodes on the Emergency of synchronization on a Neurological Complex Network

Epilepsy is a neural disorder related to intense synchronous neural activities due to increased blood flow in the cerebral cortex, causing seizures followed by fainting. Antiepileptic drugs can prevent seizures and fend off the emergence of synchrony in neural networks. However, about a third of medicated patients experience seizures again. Thus, the urge to comprehend brain dynamics and to provide a better quality of life for people with this condition motivates several scientific efforts. To this end, we modeled a feline`s cerebral cortex as a complex network. Therefore, the objective is to investigate the most influential areas of the cerebral cortex and how they influence the dynamics of synchronization associated with epilepsy. To study synchronization, the Kuramoto model was used to govern the dynamics between the areas of the cortex. We used the Hypertext Induced Topic Search (HITS) algorithm to classify internet pages and to identify the most influential nodes in the feline cerebral cortex network.

Regarding the dynamics and measures of global, mesoscopic, and microscopic synchrony, results were obtained for a scenario using the original network and two other scenarios, in which it was considered a disturbance, to simulate the action of an antiepileptic drug, the disturbance reduced the intensity of connections of a group containing random nodes and the group with nodes chosen by the HITS algorithm by 50%. Finally, the applied disturbance lagged the network’s global, microscopic, and mesoscopic levels. For future works, we aim to investigate the cat’s neural network using more sophisticated and realistic dynamics given by a Hodgkin-Huxley-type neuron.