1In the Proceedings of the 1998 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA'98), July 13-16, 1998, Las Vegas, Nevada, USA by using such a device, it will become practical to evolve 10,000 s of neural net modules and then assemble them into humanly de ned RAM based arti cial brain architectures which can be run by the CBM in real time to control robots, eg a robot kitten. Before large numbers of modules can be assembled together, it is essential that the individual modules have a good functionality and evolvability. The" CoDi-1Bit" CA based neural net model uses 1 bit binary signaling, so a representation needs to be chosen based on this fact. This paper discusses the merits and demerits of a representation that we call" Spike Interval Information Coding"(SIIC) and presents some simulation results obtained so far concerning the evolution of simple functional modules and the performance of the SIIC representation.