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Information transmission capacity of the nervous system of the arm – an information and communication engineering approach to the brachial plexus function

The arm includes a large number of nerve fibres that transfer information between the central nervous system and the receptors, muscles and glands of the arm. In the nervous system there is continuous traffic. At rest, when only the receptors send information continuously towards the central nervous system, the traffic is not as intensive as during stress, e.g. during movements of the arm, when the central nervous system sends information towards the muscles, as well. From an information and communication engineering perspective the nervous system of the arm is an information channel, the other end of which is in the central nervous system and the other end at the periphery of the arm. One principal question about such a communication system is what the maximum information transmission capacity of the channel is, e.g. how the information channel is dimensioned. The arm is a highly complex system with over sixty muscles moving it, and a huge number of sensory receptors in it. Nature has dimensioned the information channel of the arm to satisfy the requirements of the nervous system. In this thesis a specific mathematical model is built in order to evaluate the maximum information transmission capacity of the nervous system of the arm. The model handles the nervous system of the arm as an entity in the light of information theory. The model uses the physiological and functional properties of the nervous system of the arm as the input and gives the estimate of the maximum information transmission capacity as the output. The modelling yielded the result that the maximum information transmission capacity of the arm is about 10 Mbit/s. Hence, if a complete neural prosthesis of the arm were built, a single USB bus (12 Mbit/s) would suffice as a communication channel for each arm. The mathematical model developed can also be applied to other parts of the peripheral nervous system. The aim of future research is to apply the developed model comprehensively to the human peripheral nervous system and to estimate the maximum information transmission capacity of the whole human peripheral nervous system.