The Neural Simulation Language

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.

ISBN 0262731495   Pages 459 ISBN13 9780262731492 (What's this?)   Volumes 1 Publisher MIT Press Ltd   Weight (grammes) 1089 Imprint MIT Press   Published in Cambridge, Mass. Format Paperback   Series title Bradford Books Publication date 17 Jul 2002   Height (mm) 280 Library of Congress 2001056253   Width (mm) 216 DEWEY 006.32   Spine width (mm) 25 DEWEY edition DC21   Academic level Undergraduate, Postgraduate, Professional / Scholarly

		Preface
		Acknowledgments
1		Introduction		1
2		Simulation in NSL		15
3		Modeling in NSL		39
4		Schematic Capture System		69
5		User Interface and Graphical Windows		89
6		The Modeling Language NSLM		103
7		The Scripting Language NSLS		135
8		Adaptive Resonance Theory		157
9		Depth Perception		171
10		Retina		189
11		Receptive Fields		207
12		The Associative Search Network: Landmark Learning and Hill Climbing		219
13		A Model of Primate Visual-Motor Conditional Learning		225
14		The Modular Design of the Oculomotor System in Monkeys		261
15		Crowley-Arbib Saccade Model		283
16		A Cerebellar Model of Sensorimotor Adaption		305
17		Learning to Detour		319
18		Face Recognition by Dynamic Link Matching		343
App. I		NSLM Methods		373
App. II		NSLJ Extensions		387
App. III		NSLC Extensions		403
App. IV		NSLJ and NSLC Differences		411
App. V		NSLJ and NSLC Installation Instructions		415
		Bibliography		415
		Index		425

"Weitzenfeld, Arbib, and Alexander provide an excellent and durable resource--NSL--for the seasoned neural modeler. As the book amply illustrates, NSL offers great versatility for diverse applications in the study of the brain, from vision to learning to motor behavior and beyond." --Ronald C. Arkin, Professor and Director of the Mobile Robot Laboratory, College of Computing, Georgia Institute of Technology "This timely book will benefit researchers and practitioners as well as educators and students in the community of neural networks (both biologically realistic and artificial). The Neural Simulation Language offers great flexibility in building neural network models and strong object-oriented programming methodology." --DeLiang Wang, Department of Computer and Information Science and Center for Cognitive Science, The Ohio State University

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