The Neural Simulation Language: A System for Brain Modeling

The Neural Simulation Language (NSL), developed by Alfredo Weitzenfeld, Michael Arbib, and Amanda Alexander, provides a simulation environment for modular brain modeling. NSL is an object-oriented language offering object-oriented protocols applicable to all levels of neural simulation. One of NSL's main strengths is that it allows for realistic modeling of the anatomy of macroscopic brain structures.The book is divided into two parts. The first part presents an overview of neural network and schema modeling, a brief history of NSL, and a detailed discussion of the new version, NSL 3.0. It includes tutorials on several basic schema and neural network models. The second part presents models built in NSL by researchers from around the world, including those for conditional learning, face recognition, associative search networks, and visuomotor coordination.

Each chapter provides an explanation of a model, an overview of the NSL 3.0 code, and a representative set of simulation results.

An overview of the Neural Simulation Language (NSL), including examples of a rich variety of brain models.

Alfredo Weitzenfeld is Professor of Computer Science and Director of the CANNES Laboratory at the Instituto Tecnológico Autónomo de México.

Michael A. Arbib is University Professor; Fletcher Jones Professor of Computer Science; and Professor of Neuroscience, Biomedical Engineering, Electrical Engineering, and Psychology at the University of Southern California.

Amanda Alexander is a Systems Engineer at the University of Southern California.