Modeling biological neural networks

Abstract

In recent years, many new experimental studies on emerging phenomena in neural systems have been reported. The high efficiency of living neural systems to encode, process, and learn information has stimulated an increased interest among theoreticians in developing mathematical approaches and tools to model biological neural networks. In this chapter we review some of the most popular models of neurons and neural networks that help us understand how living systems perform information processing. Beyond the fundamental goal of understanding the function of the nervous system, the lessons learned from these models can also be used to build bio-inspired paradigms of artificial intelligence and robotics.