Enhanced Facilitatory Neuronal Dynamics for Delay Compensation

Our earlier work has suggested that neuronal transmission delay may cause serious problems unless a compensation mechanism exists. In that work, facilitating neuronal dynamics was found to be effective in battling delay (the facilitating activation network model, or FAN). A systematic analysis showed that the previous FAN model has a subtle problem especially when high facilitation rates are used. We derived an improved facilitating dynamics at the neuronal level to overcome this limitation. In this paper, we tested our proposed approach in 2D pole balancing controllers, where it was shown to perform better than the previous FAN model. We also systematically tested the correlation between delay duration on the one hand and facilitation rate that effectively overcome the increasing delay on the other hand. Finally, we investigated the differential utilization of facilitating dynamics in sensory vs. motor neurons and found that motor neurons utilize the facilitating dynamics more than the sensory neurons. These findings are expected to help us better understand the role of facilitation in natural and artificial agents.