Information Processing Theory and Gibson’s Theory of Perception

Topic: Cognitive Psychology
Words: 550 Pages: 2

Information processing theory is an approach to studying cognitive development, an experimental tradition in psychology. Developmental psychologists adhere to an information-processing perspective and consider mental development regarding changes during maturation in significant components of a child’s psyche (Wang & Baillargeon, 2006).The theory is based on the idea that people process the information they receive and do not just react to stimuli. This view equates the mind with a computer responsible for analyzing the environment’s information. According to the standard information processing model for mental development, the mechanisms of the mind include attentional mechanisms for inputting information, working memory for actively manipulating information, and long-term memory for passively retaining information so that it can be used in the future (Yermolayeva & Rakison, 2014).

The main components of information processing are information stores and cognitive processes. Information stores are various places where information can be stored in mind. Information is briefly stored in sensory memory: this information is stored long enough for us to move the information into short-term memory. Short-term memory can only store a small amount of information at a time. There is no limit to the amount of information stored in long-term memory (Yermolayeva & Rakison, 2014). The information stored here can be stored for many years. Finally, procedural memory consists of learned procedures or processes like riding a bicycle.

Coding, retrieval, and perception are well-known cognitive processes used to transmit information. Encoding is transferring information from short-term to long-term memory by associating long-term memory information with a short-term memory element (Yermolayeva & Rakison, 2014). Retrieval is used to return information from long-term memory to short-term memory. Perception is the use of processed information to interpret the environment.

The fundamental novelty of Gibson’s approach is that he did not consider it necessary to involve any intermediate mental mechanisms to explain the integration of disparate sensory elements into the perceptual image. He believed that the visual information that enters the retina is rich and structured enough to carry adequate and comprehensive information about the external world. Instead of the usual term “stimulus” (Pick, 1992), he introduced the concept of visual information, which is contained in the space surrounding a person.

He introduced the concept of perceiving systems, different from the traditional concept of sense organs. The perceiving system has organs, and the sense organs have receptors. The fundamental concepts that describe the work of the perceiving system are the organ and its setting, built into a hierarchical system of mutual subordination. When characterizing the perceiving system, the author pointed out that the specifics of its work directly depend on the features and properties of objects in the external world (Pick, 1992). In the process of perception, the system adjusts to the logic of the objective world to the possibilities of changing it. In Gibson’s theory of visual perception, one of the central places is occupied by the concept of invariants. A perceptual invariant is a complex property distinguished in the structure of optical information (Pick, 1992). It is expressed in the fact that it remains unchanged regardless of the changes that occur in the environment. Both information processing theory and Gibson’s theory are very important for understanding how the human brain learns. The intriguing question is, how can they be used to train non-human computing systems such as artificial intelligence?

References

Pick, H. L. (1992). Eleanor J. Gibson: Learning to perceive and perceiving to learn. Developmental Psychology, 28(5), 787–794.

Wang, S. H., & Baillargeon, R. (2006). Infants’ physical knowledge affects their change detection. Developmental science, 9(2), 173–181.

Yermolayeva, Y., & Rakison, D. H. (2014). Connectionist modeling of developmental changes in infancy: approaches, challenges, and contributions. Psychological bulletin, 140(1), 224–255.

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