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Stochastic biomathematical models are becoming increasingly important as new light is shed on the role of noise in living systems. In certain biological systems, stochastic effects may even enhance a signal, thus providing a biological motivation for the noise observed in living systems. Recent advances in stochastic analysis and increasing computing power facilitate the analysis of more biophysically realistic models, and this book provides researchers in computational neuroscience and stochastic systems with an overview of recent developments. Key concepts are developed in chapters written by experts in their respective fields. Topics include: one-dimensional homogeneous diffusions and their boundary behavior, large deviation theory and its application in stochastic neurobiological models, a review of mathematical methods for stochastic neuronal integrate-and-fire models, stochastic partial differential equation models in neurobiology, and stochastic modeling of spreading cortical depression.

Neurons --- Stochastic models --- Computational neuroscience --- Mathematical Concepts --- Statistics as Topic --- Cells --- Nervous System --- Models, Biological --- Models, Theoretical --- Epidemiologic Methods --- Anatomy --- Phenomena and Processes --- Health Care Evaluation Mechanisms --- Investigative Techniques --- Public Health --- Quality of Health Care --- Environment and Public Health --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Health Care Quality, Access, and Evaluation --- Health Care --- Models, Neurological --- Stochastic Processes --- Mathematics --- Human Anatomy & Physiology --- Health & Biological Sciences --- Physical Sciences & Mathematics --- Neuroscience --- Mathematical Statistics --- Mathematical models --- Stochastic models. --- Computational neuroscience. --- Mathematical models. --- Computational neurosciences --- Nerve cells --- Neurocytes --- Models, Stochastic --- Mathematics. --- Neurobiology. --- Probabilities. --- Statistics. --- Probability Theory and Stochastic Processes. --- Mathematical Modeling and Industrial Mathematics. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Models, Mathematical --- Simulation methods --- Neurosciences --- Math --- Science --- Computational biology --- Nervous system --- Distribution (Probability theory. --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Statistics .