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Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study
Published on: July 21, 2021
Lag Synchronization of Noisy and Nonnoisy Multiple Neurobiological Coupled FitzHugh-Nagumo Networks with and without
Malik Muhammad Ibrahim1, Shazia Iram2, Muhammad Ahmad Kamran3
1Department of Mathematics, Pusan National University, Busan 46241, Republic of Korea.
Abstract:
This paper presents a methodology for synchronizing noisy and nonnoisy multiple coupled neurobiological FitzHugh-Nagumo (FHN) drive and slave neural networks with and without delayed coupling, under external electrical stimulation (EES), external disturbance, and variable parameters for each state of both FHN networks. Each network of neurons was configured by considering all aspects of real neurons communications in the brain, i.e., synapse and gap junctions. Novel adaptive control laws were developed and proposed that guarantee the synchronization of FHN neural networks in different configurations. The Lyapunov stability theory was utilized to analytically derive the sufficient conditions that ensure the synchronization of the FHN networks. The effectiveness and robustness of the proposed control laws were shown through different numerical simulations.
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