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Bottom–up processing is a type of information processing based on incoming data from the environment to form a perception. From a cognitive psychology perspective, information enters the eyes in one direction (sensory input, or the "bottom"), and is then turned into an image by the brain that can be interpreted and recognized as a perception ...
Bottom-up processing is also known as data-driven processing, because it originates with the stimulation of the sensory receptors. [10] Psychologist James Gibson opposed the top-down model and argued that perception is direct, and not subject to hypothesis testing as Gregory proposed.
Bottom-up may refer to: Bottom-up analysis, a fundamental analysis technique in accounting and finance; Bottom-up parsing, a computer science strategy; Bottom-up processing, in Pattern recognition (psychology) Bottom-up theories of galaxy formation and evolution; Bottom-up tree automaton, in data structures; Bottom-up integration testing, in ...
McClelland and Rumelhart's parallel processing model describes perception as the meeting of top-down (conceptual) and bottom-up (sensory) elements. In the late 1990s, the idea of top-down and bottom-up processing was translated into a computational model of vision by Rao and Ballard. [3]
Researchers of this school have described two different aspects of how the mind focuses attention to items present in the environment. The first aspect is called bottom-up processing, also known as stimulus-driven attention or exogenous attention. These describe attentional processing which is driven by the properties of the objects themselves.
This is sometimes referred to as "bottom-up" processing, as it is the properties of the stimuli which affect selection. Since things that affect pre-attentive processing do not necessarily correlate with things that affect attention, stimulus salience may be more important than conscious goals.
In the top level, information processing involves passing activations among chunk nodes by means of rules and, in the bottom level, information processing involves propagating (micro)feature activations through artificial neural networks. Top-down and bottom-up information flows are enabled by links between the two levels.
During perception of any kind, people generally use either sensory data (bottom-up design) or prior knowledge of the stimulus (top-down design) when analyzing the stimulus. Individuals generally use both types of processing to examine stimuli. [4]