Connectionist Modeling and Parallel Architectures

Joachim Diederich, Queensland University of Technology (Brisbane), started with a brief introduction to connectionist modeling and parallel machines. Neural network modeling can be done on various levels of abstraction. On a low level of abstraction, a simulator can support the definition and simulation of "compartmental models," chemical synapses, dendritic trees etc., i.e. explicit computational models of single neurons. These models have been built by use of SPICE (DC Berkeley) and Genesis (Caltech). On a higher level of abstraction, the Rochester Connectionist Simulator (RCS~ University of Rochester) and ICSIM (lCSI Berkeley) allow the definition of unit types and complex connectivity patterns. On a very high level of abstraction, simulators like tleam (UCSD) allow the easy realization of pre-defined network architectures (feedforward networks) and leaming algorithms such as backpropagation.