Summary
The article offers a new view on the organization of the processes of human perception. It introduces the concept of inclusive sensory characteristic, which is a response of a given perceptual level to those features or characteristics of an underlying level whose spatial organization or specific temporal succession constitutes an adaptively meaningful entity. The sequence of inclusive characteristics forms a hierarchy: from features to the highest inclusive characteristics which bind sensory data into unified images and scenes. The highest inclusive characteristic is neither an image nor a scene, but a unique scheme of combination of underlying-level objects, which produces the image or the scene. Specific patterns of electric activity, which map inclusive characteristics, are relayed by feedbacks from upper to lower neuronal levels. This forms a cascade of top-down transfer of excitation, which stimulates those neuronal populations whose signals correspond to the highest inclusive characteristic of a given act of perception. Stimulation from above reduces the time of response of selected neurons at underlying levels to simultaneously arriving spikes to milliseconds. As a result, neuronal populations at the underlying levels, which are involved in a given act of perception, become, for a short time, coincidence detectors. The hierarchically arranged set of neuronal ensembles of coincidence detectors forms a fast sensory pathway, single and unique for each act of perception.
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Extract
Model of Perception: The Hierarchy of Inclusive Sensory Characteristics and Top-Down Cascade Transfer of Excitation
1. Introduction
Despite a long history of study of perception, the neurobiological mechanisms of its many important properties have not yet been credibly ascertained. These include the "problem of binding" : How does the brain bind sensory data into whole images and scenes and what mechanisms does it use? In models of perception, which are formulated in terms of "binding" of features, a serious difficulty is posed by the fast growth in the number of possible combinations, which leads to the problem of combinatory explosion in perception. How does the brain select a unique image, adequate to reality, from an immense multitude of possible combinations? The mechanisms of "constancy of perception" call for an explanation: Why do we perceive an object as the same even if its form, exposure, illumination and other physical characteristics change? Learning to perceive sensory categories is known to be related to the formation of authomatisms or conditioned reflexes, which requires adequate training. However, in many cases new categories are perceived very fast, literally at first sight. How can learning be so fast?To solve these and some other problems, a model of perception based on the mapping of a stimulus by a hierarchically arranged set of inclusive sensory characteristics and cascade top-down transfer of specific excitation is proposed. A computer simulation of perception confirms that the proposed model works, while theoretical corollaries of the model fit well the experimental data of the neurobiology of perception [1, 2].2. Inclusive Sensory CharacteristicsIt is known that eye retina projects into the primary cortex with a high topographic precision, and the neurons of the projection cortex have minimum receptive fields. The receptive fields of the neurons are the larger the farther up the sensory pathway they are, whereas the precision of topographic mapping decreases. This rule is valid for the entire sensory cortex: The receptive fields of the neurons are the larger the farther they are from the projection areas and the nearer to the associative areas. The neuronal structures at overlying processing levels cannot therefore map the details of the stimulus fi...See the full content of this document
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