Author: Robin A. Murphy
Publisher: Frontiers Media SA
Published: 2014-09-24
Total Pages: 113
ISBN-13: 2889192903
DOWNLOAD EBOOKTheories of associative learning have a long history in advancing the psychological account of behavior via cognitive representation. There are many components and variations of associative theory but at the core is the idea that links or connections between stimuli or responses describe important aspects of our psychological experience. This Frontiers Topic considers how variations in association formation can be used to account for differences between people, elaborating the differences between males and females, differences over the life span, understanding of psychopathologies or even across cultural contexts. A recent volume on the application of learning theory to clinical psychology is one example of this emerging application (e.g., Hazelgrove & Hogarth, 2012). The task for students of learning has been the development, often with mathematically defined explanations, of the parameters and operators that determine the formation and strengths of associations. The ultimate goal is to explain how the acquired representations influence future behavior. This approach has recently been influential in the field of neuroscience where one such learning operator, the error correction principle, has unified the understanding of the conditions which facilitate neuron activation with the computational goals of the brain with properties of learning algorithms (e.g., Rescorla & Wagner, 1972). In this Frontiers Research Topic, we are interested in a similar but currently developing aspect to learning theory, which is the application of the associative model to our understanding of individual differences, including psychopathology. In general, learning theories are monolithic, the same theory applies to the rat and the human, and within people the same algorithm is applied to all individuals. If so this might be thought to suggest that there is little that learning theory can tell us about the how males and females differ, how we change over time or why someone develops schizophrenia for instance. However, these theories have wide scope for developing our understanding of when learning occurs and when it is interfered with, along with a variety of methods of predicting these differences. We received contributions from researchers studying individual differences, including sex differences, age related changes and those using analog or clinical samples of personality and psychopathological disorders where the outcomes of the research bear directly on theories of associative learning. This Research Topic brings together researchers studying basic learning and conditioning processes but in which the basic emotional, attentional, pathological or more general physiological differences between groups of people are modeled using associative theory. This work involves varying stimulus properties and temporal relations or modeling the differences between groups.
Book Synopsis Individual differences in associative learning by : Robin A. Murphy
Download or read book Individual differences in associative learning written by Robin A. Murphy and published by Frontiers Media SA. This book was released on 2014-09-24 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theories of associative learning have a long history in advancing the psychological account of behavior via cognitive representation. There are many components and variations of associative theory but at the core is the idea that links or connections between stimuli or responses describe important aspects of our psychological experience. This Frontiers Topic considers how variations in association formation can be used to account for differences between people, elaborating the differences between males and females, differences over the life span, understanding of psychopathologies or even across cultural contexts. A recent volume on the application of learning theory to clinical psychology is one example of this emerging application (e.g., Hazelgrove & Hogarth, 2012). The task for students of learning has been the development, often with mathematically defined explanations, of the parameters and operators that determine the formation and strengths of associations. The ultimate goal is to explain how the acquired representations influence future behavior. This approach has recently been influential in the field of neuroscience where one such learning operator, the error correction principle, has unified the understanding of the conditions which facilitate neuron activation with the computational goals of the brain with properties of learning algorithms (e.g., Rescorla & Wagner, 1972). In this Frontiers Research Topic, we are interested in a similar but currently developing aspect to learning theory, which is the application of the associative model to our understanding of individual differences, including psychopathology. In general, learning theories are monolithic, the same theory applies to the rat and the human, and within people the same algorithm is applied to all individuals. If so this might be thought to suggest that there is little that learning theory can tell us about the how males and females differ, how we change over time or why someone develops schizophrenia for instance. However, these theories have wide scope for developing our understanding of when learning occurs and when it is interfered with, along with a variety of methods of predicting these differences. We received contributions from researchers studying individual differences, including sex differences, age related changes and those using analog or clinical samples of personality and psychopathological disorders where the outcomes of the research bear directly on theories of associative learning. This Research Topic brings together researchers studying basic learning and conditioning processes but in which the basic emotional, attentional, pathological or more general physiological differences between groups of people are modeled using associative theory. This work involves varying stimulus properties and temporal relations or modeling the differences between groups.
