In this paper we describe a shell which has been developed to allow an integration of neural network and expert systems technology. The system, SCRuFFy, is based on an analysis of the different abilities and time courses of NN and AI systems. Critical to the processing of this system is a temporal pattern matcher which is used to mediate between the two subsystems, providing a "signal to symbol" mapping. This mapping allows the expert system to reason about the time course of signals which are classified by a connectionist network which is trained via classical back-propagation of error during a separate training phase. An example of the simulated control of the temperature of an underwater welding robot is presented to demonstrate these capabilities.