Skip navigation

Michael A. Arbib

Michael A. Arbib is University Professor, Fletcher Jones Professor of Computer Science, and Professor of Biological Sciences, Biomedical Engineering, Electrical Engineering, Neuroscience, and Psychology at the University of Southern California. He is the author or editor of many books, including The Handbook of Brain Theory and Neural Networks (MIT Press, second edition 2002).

Titles by This Author

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.

Structure, Function, and Dynamics

In Neural Organization, Arbib, Érdi, and Szentágothai integrate structural, functional, and dynamical approaches to the interaction of brain models and neurobiologcal experiments. Both structure-based "bottom-up" and function-based "top-down" models offer coherent concepts by which to evaluate the experimental data. The goal of this book is to point out the advantages of a multidisciplinary, multistrategied approach to the brain.

Titles by This Editor

A Mysterious Relationship

This book explores the relationships between language, music, and the brain by pursuing four key themes and the crosstalk among them: song and dance as a bridge between music and language; multiple levels of structure from brain to behavior to culture; the semantics of internal and external worlds and the role of emotion; and the evolution and development of language. The book offers specially commissioned expositions of current research accessible both to experts across disciplines and to non-experts.

Dramatically updating and extending the first edition, published in 1995, the second edition of The Handbook of Brain Theory and Neural Networks presents the enormous progress made in recent years in the many subfields related to the two great questions: How does the brain work? and, How can we build intelligent machines?