This article addresses a process of perception based on a methodical, in this case, algorithmic approach. As such, it is a type of standardized procedure that controls the formalaesthetic elements of this process step by step, analyzing their colors, forms and patterns of movements and spatial direction, etc - a procedure that seeks to compare and find a common denominator. When accompanied by other signals, the non-linear and quantized, i.e. encoded, input signals that regularly initiate this procedure, overlap as they progress. Consequentially, they have to combine and compensate frequencies, similar to a quantum physical ‘superposition’, by means of compensatory variables, e.g. affective design elements, ultimately achieving a common denominator. This procedure, which largely derives from what is known as ‘Deep Learning’ (Schmidhuber 2014) and Stevan Harnad’s theory of categorization, has proved extremely valuable in pictorial art work with people affected by neuronal damage and dementia. The failure of entire areas of the brain forces these people to coordinate the visual, sound, sensory and motor waves characterized by frequencies at the remaining interfaces during the normal automated search recognition process. According to quantum physicist Fischbeck (2000), the neuronal search process is supported and compensated, for example in cases of distress, by aesthetic-emotional forms. These usually guarantee the semantic coherence of forms of consciousness and perception, oriented in this context to place and grid cells and motor neurons, which essentially control entire areas of corresponding cells in the hippocampal/entorhinal and motor cortex (Bellmund and Doeller 2019).