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Inspired by biological cognition, CABOT project explores the ways symbolic processing can emerge in a system of neural cell assemblies (CAs). Here we show how a stochastic meta--control process can regulate learning of associations between the CAs, the neural basis of symbols. An experiment illustrates the learning between CAs representing conditions actions pairs, which leads to CA--based representations of 'if--then' rules.

Emergence of Rules in Cell Assemblies of fLIF Neurons