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"Models, Neurological"
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Integrated models of cognitive systems
The field of cognitive modeling has progressed beyond modeling cognition in the context of simple laboratory tasks and begun to attack the problem of modeling cognition in more complex, realistic environments, such as those studied by researchers in the field of human factors. The problems that the human-factors community is tackling focus on modeling certain problems of communication and control that arise in the integration of implicit and explicit knowledge, emotion, and cognition, and the cognitive system with the external environment. These problems must be addressed in order to produce integrated cognitive models of moderately complex tasks. Architectures of cognition in these tasks focus on the control of a central system, which includes control of the central processor itself, initiation of functional processes, such as visual search and memory retrieval, and harvesting the results of functional processes. Because the control of the central system is conceptually different from the internal control required by individual functional processes, a complete architecture of cognition must incorporate two types of theories of control: type 1 theories of the structure, functionality, and operation of the controller, and type 2 theories of the internal control of functional processes, how, and what they communicate to the controller. This volume presents, for both types of theories, the current state of the art, as well as contrasts among current approaches to human-performance models.
eBook
Neural control engineering : the emerging intersection between control theory and neuroscience
How powerful new methods in nonlinear control engineering can be applied to neuroscience, from fundamental model formulation to advanced medical applications.Over the past sixty years, powerful methods of model-based control engineering have been responsible for such dramatic advances in engineering systems as autolanding aircraft, autonomous vehicles, and even weather forecasting. Over those same decades, our models of the nervous system have evolved from single-cell membranes to neuronal networks to large-scale models of the human brain. Yet until recently control theory was completely inapplicable to the types of nonlinear models being developed in neuroscience. The revolution in nonlinear control engineering in the late 1990s has made the intersection of control theory and neuroscience possible. In Neural Control Engineering, Steven Schiff seeks to bridge the two fields, examining the application of new methods in nonlinear control engineering to neuroscience. After presenting extensive material on formulating computational neuroscience models in a control environment-including some fundamentals of the algorithms helpful in crossing the divide from intuition to effective application-Schiff examines a range of applications, including brain-machine interfaces and neural stimulation. He reports on research that he and his colleagues have undertaken showing that nonlinear control theory methods can be applied to models of single cells, small neuronal networks, and large-scale networks in disease states of Parkinson's disease and epilepsy. With Neural Control Engineering the reader acquires a working knowledge of the fundamentals of control theory and computational neuroscience sufficient not only to understand the literature in this trandisciplinary area but also to begin working to advance the field. The book will serve as an essential guide for scientists in either biology or engineering and for physicians who wish to gain expertise in these areas.
eBook
Neurobiology of attention
A key property of neural processing in higher mammals is the ability to focus resources by selectively directing attention to relevant perceptions, thoughts or actions.Research into attention has grown rapidly over the past two decades, as new techniques have become available to study higher brain function in humans, non-human primates, and other.
eBook
Peripheral nervous system plasmalogens regulate Schwann cell differentiation and myelination
Rhizomelic chondrodysplasia punctata (RCDP) is a developmental disorder characterized by hypotonia, cataracts, abnormal ossification, impaired motor development, and intellectual disability. The underlying etiology of RCDP is a deficiency in the biosynthesis of ether phospholipids, of which plasmalogens are the most abundant form in nervous tissue and myelin; however, the role of plasmalogens in the peripheral nervous system is poorly defined. Here, we used mouse models of RCDP and analyzed the consequence of plasmalogen deficiency in peripheral nerves. We determined that plasmalogens are crucial for Schwann cell development and differentiation and that plasmalogen defects impaired radial sorting, myelination, and myelin structure. Plasmalogen insufficiency resulted in defective protein kinase B (AKT) phosphorylation and subsequent signaling, causing overt activation of glycogen synthase kinase 3β (GSK3β) in nerves of mutant mice. Treatment with GSK3β inhibitors, lithium, or 4-benzyl-2-methyl-1,2,4-thiadiazolidine-3,5-dione (TDZD-8) restored Schwann cell defects, effectively bypassing plasmalogen deficiency. Our results demonstrate the requirement of plasmalogens for the correct and timely differentiation of Schwann cells and for the process of myelination. In addition, these studies identify a mechanism by which the lack of a membrane phospholipid causes neuropathology, implicating plasmalogens as regulators of membrane and cell signaling.
Journal Article
Mathematics for neuroscientists
Virtually all scientific problems in Neuroscience require mathematical analysis, and all neuroscientists are increasingly required to have a significant understanding of mathematical methods. There is currently no comprehensive, integrated introductory book on the use of mathematics in Neuroscience, existing books either concentrate solely on theoretical modeling or discuss mathematical concepts for the treatment of very specific problems. This book fills this need by systematically introducing mathematical and computational tools in precisely the contexts that first established their importance for neuroscience.
eBook