Theoretical neuroscience refers to a subfield of neuroscience which makes use of brain abstractions, mathematical models and theoretical analysis. It provides a quantitative foundation to explain what nervous systems do, determines how they work and discovers the underlying general principles of their operation. Computational modelling and theoretical analysis are useful tools for describing what nervous systems do, figuring out how they work and understanding why they do so in a specific manner. Neuroscience includes a wide range of methods from molecular and cellular research as well as human, psychophysics and psychology. Theoretical neuroscience promotes cross-disciplinary collaboration through creating compact representations of what has been learned, bridging the gap among different levels of description and recognizing unifying concepts and principles. The basic function of computational modeling neuroscience is to understand the principles governing the development, structure, physiology and cognitive abilities of the nervous system. The goal of models in theoretical neuroscience is to capture the key characteristics of the biological system at multiple spatial-temporal scales. This book is a valuable compilation of topics, ranging from the basic to the most complex advancements in the field of theoretical neuroscience. It aims to shed light on the computational and mathematical modeling of neural systems. The book is appropriate for those seeking detailed information in this area.