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The lack of scientists equally trained and prepared to understand both mathematics and biology/medicine hampers the development and application of computer simulation methods in biology and neurogastrobiology. Currently, there are no texts for navigating the extensive and intricate field of mathematical and computational modeling in neurogastrobiology. This book bridges the gap between mathematicians, computer scientists and biologists, and thus assists in the study and analysis of complex biological phenomena that cannot be done through traditional in vivo and in vitro experimental approaches. The book recognizes the complexity of biological phenomena under investigation and treats the subject matter with a degree of mathematical rigor. Special attention is given to computer simulations for interpolation and extrapolation of electromechanical and chemoelectrical phenomena, nonlinear self-sustained electromechanical wave activity, pharmacological effects including co-localization and co-transmission by multiple neurotransmitters, receptor polymodality, and drug interactions. Mathematical Modeling and Simulation in Enteric Neurobiology is an interdisciplinary book and is an essential source of information for biologists and doctors who are interested in knowing about the role and advantages of numerical experimentation in their subjects, as well as for mathematicians who are interested in exploring new areas of applications.
The lack of scientists equally trained and prepared to understand both mathematics and biology/medicine hampers the development and application of computer simulation methods in biology and neurogastrobiology. Currently, there are no texts for navigating the extensive and intricate field of mathematical and computational modeling in neurogastrobiology. This book bridges the gap between mathematicians, computer scientists and biologists, and thus assists in the study and analysis of complex biological phenomena that cannot be done through traditional in vivo and in vitro experimental approaches.The book recognizes the complexity of biological phenomena under investigation and treats the subject matter with a degree of mathematical rigor. Special attention is given to computer simulations for interpolation and extrapolation of electromechanical and chemoelectrical phenomena, nonlinear self-sustained electromechanical wave activity, pharmacological effects including co-localization and co-transmission by multiple neurotransmitters, receptor polymodality, and drug interactions.Mathematical Modeling and Simulation in Enteric Neurobiology is an interdisciplinary book and is an essential source of information for biologists and doctors who are interested in knowing about the role and advantages of numerical experimentation in their subjects, as well as for mathematicians who are interested in exploring new areas of applications.
Mathematical modelling of physiological systems promises to advance our understanding of complex biological phenomena and pathophysiology of diseases. In this book, the authors adopt a mathematical approach to characterize and explain the functioning of the gastrointestinal system. Using the mathematical foundations of thin shell theory, the authors patiently and comprehensively guide the reader through the fundamental theoretical concepts, via step-by-step derivations and mathematical exercises, from basic theory to complex physiological models. Applications to nonlinear problems related to the biomechanics of abdominal viscera and the theoretical limitations are discussed. Special attention is given to questions of complex geometry of organs, effects of boundary conditions on pellet propulsion, as well as to clinical conditions, e.g. functional dyspepsia, intestinal dysrhythmias and the effect of drugs to treat motility disorders. With end of chapter problems, this book is ideal for bioengineers and applied mathematicians.
The idea of preparing this volume originated from the ever increasing importance of computational modelling of complex problems in medicine. Considerable advances have been made in this area as demonstrated by the continued success of the International Conference on Modelling in Medicine and Biology organised by the Wessex Institute of Technology.The work reported at those meetings and the research carried out at the Wessex Institute of Technology indicated the increasing interaction and collaboration between medical and engineering scientists. Advances presented at these conferences are now being used in practice for a wide range of medical and surgical applications.The considerable improvements and evolution of the field has led to some of the best scientists, who have participated in our conferences, to write an article on their most recent research. This has led to thirteen outstanding articles published in this volume which encompass important areas of biomedical modelling.
Featuring contributions from the eighth International Conference on Modelling in Medicine and Biology, this volume covers a broad spectrum of topics including the application of computers to simulate biomedical phenomena. It will be of interest to medical and physical scientists and engineers.
This book contains contributions from the tenth International Conference on Modelling in Medicine and Biology. The advances covered in the computer modelling, and computational methods and measurements, and their integration, have applications in the study of orthopaedics, cardiovascular systems biomechanics and electrical simulation, amongst others, and are leading to progress in medical care and treatment.
Mathematics for Neuroscientists, Second Edition, presents a comprehensive introduction to mathematical and computational methods used in neuroscience to describe and model neural components of the brain from ion channels to single neurons, neural networks and their relation to behavior. The book contains more than 200 figures generated using Matlab code available to the student and scholar. Mathematical concepts are introduced hand in hand with neuroscience, emphasizing the connection between experimental results and theory. - Fully revised material and corrected text - Additional chapters on extracellular potentials, motion detection and neurovascular coupling - Revised selection of exercises with solutions - More than 200 Matlab scripts reproducing the figures as well as a selection of equivalent Python scripts
Modeling and Simulation in Python teaches readers how to analyze real-world scenarios using the Python programming language, requiring no more than a background in high school math. Modeling and Simulation in Python is a thorough but easy-to-follow introduction to physical modeling—that is, the art of describing and simulating real-world systems. Readers are guided through modeling things like world population growth, infectious disease, bungee jumping, baseball flight trajectories, celestial mechanics, and more while simultaneously developing a strong understanding of fundamental programming concepts like loops, vectors, and functions. Clear and concise, with a focus on learning by doing, the author spares the reader abstract, theoretical complexities and gets right to hands-on examples that show how to produce useful models and simulations.
This book shows how to develop efficient quantitative methods to characterize neural data and extra information that reveals underlying dynamics and neurophysiological mechanisms. Written by active experts in the field, it contains an exchange of innovative ideas among researchers at both computational and experimental ends, as well as those at the interface. Authors discuss research challenges and new directions in emerging areas with two goals in mind: to collect recent advances in statistics, signal processing, modeling, and control methods in neuroscience; and to welcome and foster innovative or cross-disciplinary ideas along this line of research and discuss important research issues in neural data analysis. Making use of both tutorial and review materials, this book is written for neural, electrical, and biomedical engineers; computational neuroscientists; statisticians; computer scientists; and clinical engineers.