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In this paper an enhancement of the categorizing and learning module (CALM) is presented. The CALM neural network module was used as a basic building block of the more complex neural network for vision. The CALM module stands there as a model of cortical columns, which compose the primary visual cortex. The main disadvantage of the basic CALM model found in the previous research is that the module is not capable to detect a change of input signal automatically, which cannot be satisfactory from the biological point of view. We describe certain modifications of the structure and behavior of the module that make the model more autonomous and suitable for the modeling of the human visual cortex.