![]() Psychologist Richard Gregory (1970) argued that perception is a constructive process that relies on top-down processing. Gregory (1970) and Top-Down Processing Theory This is because the meaning of the surrounding words provides a context to aid understanding. For example, understanding difficult handwriting is easier when reading complete sentences than reading single and isolated words. Top-down processing refers to the use of contextual information in pattern recognition. Processing is carried out in one direction from the retina to the visual cortex, with each successive stage in the visual pathway carrying out an ever more complex analysis of the input. Psychologists distinguish between two types of processes in perception: bottom-up processing and top-down processing.īottom-up processing is also known as data-driven processing because perception begins with the stimulus itself. This controversy is discussed with respect to Gibson (1966), who has proposed a direct theory of perception which is a “bottom-up” theory, and Gregory (1970), who has proposed a constructivist (indirect) theory of perception which is a “top-down” theory. Some argue that perceptual processes are not direct but depend on the perceiver’s expectations and previous knowledge as well as the information available in the stimulus itself. Sensory inputs are somehow converted into perceptions of desks and computers, flowers and buildings, cars and planes, into sights, sounds, smells, tastes, and touch experiences.Ī major theoretical issue on which psychologists are divided is the extent to which perception relies directly on the information present in the environment. Each sense organ is part of a sensory system that receives sensory inputs and transmits sensory information to the brain.Ī particular problem for psychologists is explaining how the physical energy received by sense organs forms the basis of perceptual experience. To receive information from the environment, we are equipped with sense organs, e.g., the eye, ear, and nose. ![]()
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