Grouping, segmentation, and accentuation - processes involved in stimulus perception - are discussed. These effects are explained in terms of the universal vector coding model in neural networks. Grouping is the combination of objects or events into units on the basis of their similarity. Segmentation, conversely, is the separation of groups to the level of ensembles consisting of small numbers of objects. The processes of grouping and segmentation are regarded from the point of view of their underlying neural mechanisms. It is suggested that stimuli in neural networks are encoded by patterns of excitation of cardinal neurons. These excitation patterns can be represented as excitation vectors. Differences between stimuli are formed as the absolute magnitudes of their vector differences. The greater the perceived stimuli differ from each other, the greater the difference in their perceptual and semantic excitation vectors. The more similar the stimuli, the smaller their vector difference. This suggests that stimuli with similar excitation vectors will be grouped together in perceptual space. Conversely, stimuli with different excitation vectors will "repel" and become segmented. The spatial separation of objects increases with increases in the differences between their spatial excitation vectors. The universality of the vector coding principle can be illustrated using color contrast as an example: differences in contrasting colors increase with increases in the differences between their excitation vectors. Groups of objects with similar excitation vectors are accentuated in perception by means of summation of their excitation vectors. Groups of objects with different excitation vectors undergo mutual accentuation because of the appearance of contrast. Plastic accentuation is associated with the novelty of stimuli and is extinguished on repetition of the stimulus.

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http://dx.doi.org/10.1007/s11055-010-9255-yDOI Listing

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