An artificial model for biological computation and control for a locomotion system
E. Curran, K. Wooten, R.W. Newcomb · 2002
Each discipline has its own methods of modeling its components and developing the mathematical analysis of the systems which they want to describe. Investigating these systems from different perspectives can provide a means of discovering system operation. Specifically, when approaching the reverse engineering of a biological system, the best description of the elements should include the biological parameters and their known relationships. The modeling should be carefully tied to the biological experimental data and the results of the simulations should provide outputs comparable with actual output data from the original system. Once the model has been thoroughly tested, the mathematical description of the model can be redefined with new variables of interest for the discipline involved. This paper describes the design of a neural network capable of providing simulated output comparable to the deafferented flight neural control behaviour of the locust, using GENESIS (General Neural Simulation System).