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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.
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