Computational Modeling of Neural Activity

Computational modeling for neural activity refers to the use of computers to simulate and study complex systems using mathematics, computer science, and physics. In biology, these models integrate different data sets in a coherent and unified computational framework in order to explain certain neuroscience phenomena including neurological disorders such as dyslexia, depression, post-traumatic stress disorder (PTSD), and schizophrenia. Computation models predict disease progression through the study of molecular processes, cell to cell interactions, and the manner in which these changes affect tissues and organs. In recent years, a number of computational tools including NEURON, BRIAN, NEST, and the virtual brain (TVB), have been developed to create, validate, and investigate models of brain networks. This book is a compilation of chapters that discuss the most vital concepts and emerging trends in the area of computational modeling for neural activity. It is a collective contribution of a renowned group of international experts. The book, with its detailed analyses and data, will prove immensely beneficial to professionals and students involved in this area at various levels.