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.
