How individuals are able to obtain knowledge is something that psychologists have studied for a number of years. The ability to store and retrieve knowledge provides individuals with the propensity to form logical thought, express emotions and internalize the world around them. In order for a psychologist to understand the theories of knowledge it is necessary to investigate the aspects of the theories. In this
paper we examine the history, the basic construct, the similarities of the theories and how those theories relate to psychological therapies. History of the theories
The neural network model attempts to explain that which is known about the retention and retrieval of knowledge. Neural network models have been examined for a number of years. In the mid 1940's and 1950's the first of the network models began to appear. These publications introduced the first models of neural networks as computing machines, the basic model of a self-organizing network (Arbib, 1995).
In 1943 McCulloch and Pitts published their model theory ( Arbib, 1995). In 1948 Rashevsky proposed a number of neural network models to explain psychological phenomena. During this era not enough was known about the brain, subsequently he was considered ahead of his time. Rashevsky relied heavily upon complex mathematical equations within his model, consequently many people simply did not understand his theoretical perspective ( Martindale, 1991). In 1958 Rosenblatt proposed his theory on neural network models which focused on perception. The theory elicited a great deal of interest; however it was considered too simple to sufficiently explain all aspects of perception (Arbib, 1995).
As a result of the lack of acceptance, neural network models «fell out of fashion»(Martindale, 1991, P.12). For a nine year lapse no neural network model theories were developed. In 1967 the network approach was again examined. Konorski developed a useful network model that focused primarily on Pavlovian conditioning as opposed to
cognition. Grossberg developed his neural network theory during the years of 1969, 1980, 1987, and 1988. Grossberg developed a powerful network theory of the mind but, like the Rashevsky model, Grossberg's theory was comprised of complex mathematical terms and was therefore extremely difficult to understand. His neural network models are only now being recognized as truly revolutionary (Martindale, 1991).
Many new theorists would enter the field of neural network models, but it was the work of Rumelhart, Hinton, and McClelland that would simplify the way we would view such models (Arbib, 1995). It was in 1986 that Rumelhart, Hinton, and McClelland developed their network model. It was and still is regarded as one of the most notable network theories. This is true because they structured their theory in a clear, concise, and intelligible manner (Martindale,1991).
Neural network models have evolved during the past sixty years. The initial theories were extremely difficult to comprehend and they were not interchangeable with a broad range of topics. Today's theories are simpler to understand because they are less complex. The theories are capable of encompassing numerous topics.
The dual coding approach is one that believes that knowledge is a series of complex associative networks. Within these networks we find imaginal and verbal representations. These verbal and nonverbal representations are means that facilitate the retrieval and storage of knowledge (Paivio, 1986).
The individual who was at the fore front of the development of the dual coding theory was Allan Paivio. He did research in the area of verbal and nonverbal representations during the 1960's. Research papers that dealt with topics of verbal and imaginal processes were: Abstractness, imagery, and meaningfulness in paired-associated learning (1965) ; Latency of verbal associations and imagery to noun stimuli as a function abstractness and generality (1966) and; Mental imagery in associative learning and memory (1969), ( Paivio, 1986). In 1971 Allan Paivio presented his revolutionary paper, Imagery and Verbal Processes. As a result of this paper the concept of a dual coding process was conceived.
Paivio's subsequent paper in 1985, Mental Representations, retained the same constructive empiricism and the same basic theoretical assumptions as the earlier paper, Imagery and Verbal Processes. In this paper Paivio demonstrated that the fundamentals of a dual coding approach have stood up well to challenges over the years ( Paivio, 1986).
The dual coding process offers a clear explanation of how individuals are able to store and retrieve knowledge. Through Paivio's dual coding approach we are able to see how internal networks of verbal and imaginal representations are capable of logging and retrieving information both nonverbally and verbally.
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Comparisons and contrasts To have complete understanding of these two theories is important to compare and contrast them. It is important because commonalities allow for similar explanations of mental phenomena.
Both theories do an exceptional job of explaining the processes of the of the mind. One similarity between neural network theory and dual coding theory is that they both Construct of the theories There are a number of theories that explain how it is the human brain is capable of storing and retrieving information. A neural network model of cognition aims at explaining how and why we experience such mental phenomena.
The metaphor «the mind works like a computer» has been heard by everyone at one time or another. Can Economics Really be Considered a Science? This is a question that has been debated for decades. Why do we describe economics as a ‘science’ when it is the study of human behavior, why not class it within the arts or humanities? Economists argue that they analyze problems such as developing human behavior theories and test them against the facts using a Positivism Positivism is the belief that "scientific naturalism" is the foundation of knowledge and truth. Leszek Kolakowski wrote "Positivism is a normative attitude, regulating how we are to use such terms as 'knowledge','science','cognition', and 'information'. Positivism rejects the theories of theology and metaphysics because they don't have proof that they are true.
Positivism is a philosophy that Ai – Edge Of Excellence Running head: The Edge of Excellence The Edge of Excellence Kathleen P. Munn Community College of Philadelphia Recently, the media has spent an increasing amount of broadcast time on new technology. The focus of high-tech media has been aimed at the flurry of advances concerning artificial intelligence (AI). What is artificial intelligence and what is