Nexus: A neural simulator for integrating top-down and bottom-up modeling

Paul Sajda, K. Sakai, S.C. Yen, L. H. Finkel

We have developed the NEXUS simulation environment as a tool for modeling large-scale neural systems. The software is written in C and runs under UNIX. A unique aspect of NEXUS is that it is particularly suited for simulating hybrid neural models (i.e. systems integrating different modeling paradigms and/or architectures.1) NEXUS is designed for large-scale simulations, and to facilitate model development, testing and analysis it incorporates several major features: network architectures based on topographic maps, programmable neural units, scalable and modular simulation, support for common learning paradigms including the generalized Hebb rule and backpropagation, and a user-friendly interface. These features make NEXUS a useful environment in which to study the “perceptual” properties of various network architectures.

Accepted 1 January 1994
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