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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 ...
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]
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.
The cohort model relies on several concepts in the theory of lexical retrieval. The lexicon is the store of words in a person's mind; [3] it contains a person's vocabulary and is similar to a mental dictionary. A lexical entry is all the information about a word and the lexical storage is the way the items are stored for peak retrieval.
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 ...
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.
A highly recognized bottom-up hierarchical theory is James DiCarlo's Untangling description [6] whereby each stage of the hierarchically arranged ventral visual pathway performs operations to gradually transform object representations into an easily extractable format. In contrast, an increasingly popular recognition processing theory, is that ...
Individuals generally use both types of processing to examine stimuli. [4] The use of both sensory data and prior knowledge to reach a conclusion is a feature of optimal probabilistic reasoning, known as Bayesian inference ; cognitive scientists have shown mathematically how context effects can emerge from the Bayesian inference process.