Brain stem - from general view to computational model based on switchboard rules of operation

Despite great progress in understanding the functions and structures of the central nervous system (CNS) the brain stem remains one of the least understood systems. We know that the brain stem acts as a decision station preparing the organism to act in a specific way, but such functions are rather difficult to model with sufficient precision to replicate experimental data due to the scarcity of data and complexity of large-scale simulations of brain stem structures. The approach proposed in this article retains some ideas of previous models, and provides more precise computational realization that enables qualitative interpretation of the functions played by different network states. Simulations are aimed primarily at the investigation of general switching mechanisms which may be executed in brain stem neural networks, as far as studying how the aforementioned mechanisms depend on basic neural network features: basic ionic channels, accommodation, and the influence of noise.