Motivation Effort And The Neural Network Model


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Motivation, Effort, and the Neural Network Model


Motivation, Effort, and the Neural Network Model

Author: Theodore Wasserman

language: en

Publisher: Springer Nature

Release Date: 2020-10-27


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Our understanding of how the human brain operates and completes its essential tasks continues is fundamentally altered from what it was ten years ago. We have moved from an understanding based on the modularity of key structural components and their specialized functions to an almost diametrically opposed, highly integrated neural network model, based on a vertically organized brain dependent on small world hub principles. This new understanding completely changes how we understand essential psychological constructs such as motivation. Network modeling posits that motivation is a construct that describes a modified aspect of the operation of the human learning system that is specifically designed to cause a person to pursue a goal. Anthropologically and developmentally, these goals were initially basic, including things like food, shelter and reproduction. Over the course of time and development they develop into a complex web of extrinsic and then intrinsic goals, objectives and values. The core for all of this development is the inborn flight or fight reaction has been modified over time by a combination of inborn human temperamental characteristics and life experiences. This process of modification is, in part, based on the operation of a network based error-prediction network working in concert with the reward network to produce a system of ever evolving valuations of goals and objectives. These valuations are never truly fixed. They are constantly evolving, being modified and shaped by experience. The error prediction network and learning related networks work in concert with the limbic system to allow affect laden experiences to inform the process of valuation. These networks, operating in concert, produce a cognitive process we call motivation. Like most networks, the motivation system of networks is recruited when the task demands of the situation require them. Understanding motivation from this perspective has profound implications for many scientific disciplines in general and psychology in specific. Psychologically, this new understanding will alter how we understand client behavior in therapy and when being evaluated. This new understanding will provide direction for new therapeutic intervention for a variety of disorders of mental health. It will also inform testing practices concerning the evaluation of effort and malingering. This book is not a project in reductionism. It is the polar opposite. A neural network understanding of the operation of the human brain allows for the integration of what has come before into a comprehensive and integrated model. It will likely provide the basis for future research for years to come.

Apraxia: The Neural Network Model


Apraxia: The Neural Network Model

Author: Theodore Wasserman

language: en

Publisher: Springer Nature

Release Date: 2023-01-26


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The work will be a reanalysis and reconceptualization of the concept of apraxia. Apraxia is currently understood as a motor speech disorder but an analysis of the neural network properties of apraxia indicate a more complex and far reaching disorder with implications for intentionality, motor coordination and motor control of response inhibition in a variety of human behavioral and emotional reactions. A thorough redefinition of apraxia will be provided along with suggestions for diagnoses and treatment. The primary audience will be diagnostic and treating professionals in a variety of disciplines (outlined above). Secondarily, the book will provide an argument and justification for considering developmental apraxia pf speech to be a separate and discrete white matter based disorder. Finally, this work will serve as a driver of future research in the area.

From Theory of Knowledge Management to Practice


From Theory of Knowledge Management to Practice

Author: Fausto Pedro García Márquez

language: en

Publisher: BoD – Books on Demand

Release Date: 2024-01-31


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From Theory of Knowledge Management to Practice is a collaborative compilation featuring contributions from various authors. The book amalgamates analytical principles with the practical aspects of knowledge management in the business realm. Its unique contribution lies in bridging the gap between engineering/technology disciplines and the organizational, administrative, and planning dimensions of knowledge management. This integration is particularly valuable when viewed in conjunction with other sub-disciplines like economics, finance, marketing, and decision and risk analysis, among others. The book not only introduces but also illustrates knowledge management theories through practical case studies. These case studies showcase significant outcomes across different sectors, drawing on diverse real-world scenarios. The theoretical framework is accompanied by relevant analytical techniques, adopting a progressive approach that transitions from basic concepts to intricate and dynamic decision-making processes involving multiple data points, including big data and extensive datasets. The integration of computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization further enhances the book's utility, offering expert support for the analysis of multi-criteria decision-making problems characterized by specific constraints and requirements.