A Potentially Powerful Connectionist Unit: The Cortical Column

We propose a novel approach to neuron-like models that consists in simulating cortical columns, i.e. associations of elementary neurons having a specific, functionnal activity. This model is built according to a theory which is consistent with neurobiological data. It provides autonomous units, each computing its output as a function of its inputs, modulated by such internal features as learning coefficients.