Brain modelling for teaching, learning and research

In recent years engineering research has embarked on a wide stage of multidisciplinary fields. Boundaries of engineering disciplines have been blurred by researchers outreaching for knowledge complementary to their disciplines in fierce attempts to solve problems and further technological developments. Mathematical models of physical systems and their implementations through the software programming are the safe working grounds for us, engineering researchers. Engineers can easily understand the behaviour of a physical system from the simulation results of its mathematical model. However, engineers are not very familiar with biological systems. Neuroscience is a new emerging field which is already attracting engineers trying to understand the ways the human brain functions in order to implement the new concepts into human-made systems to make them operate more effectively, thus advancing the well known modern field of artificial intelligence. This paper is an overview of what we have learned on our journey through the computational neuroscience concepts, biologically based models of human brain functions and how they can be linked to human behaviour. It also shows some of the most interesting simulation results from our own modelling of human brain. In the last section of the paper we show how we recognised that learning occurs in a process very similar to resonance, which is a familiar concept in engineering, and how understanding of the Adaptive Resonance Theory (ART) (Carpenter & Grossberg, 2003), as a model of human learning at neuronal level, helped us to better understand the learning process itself.