This book investigates the latest advancements and diverse applications within the interdisciplinary field of neural computation. It draws upon contributions from leading experts and extended papers from the 2005 International Conference on Natural Computation, offering insights into theoretical frameworks, biologically plausible modeling, computational cognitive science, and artificial neural networks. The work aims to showcase progress across various sub-fields, highlighting how neural computation serves as a methodology for understanding brain functions, cognitive processes, and solving complex real-world problems.

The book compiles recent progress in neural computation from various disciplines, reflecting contributions from experts and extended conference papers. Its scope covers theoretical aspects, biological modeling, cognitive science applications, and the architecture and learning of artificial neural networks. The collection aims to provide a comprehensive overview of the field's advancements and its utility in addressing practical challenges.