Abstract
Neuroscience has become a vast field. Within it the modelling of neural systems is a small corner. Within that small corner the portion attending to stochastic effects is again small. Nevertheless it is a large topic, and we will tell you about only a subset that we happen to know something about. A lot of basic work has been done by researchers with limited background in probability, and simulation, as a method, is far ahead of stochastic analysis. The result is a field rich in opportunity for probabilists. We will tell you about constructions and results, trying to supply details to the extent necessary to get you started thinking about problems. These problems will be labeled with the symbol \(\mathcal{P}\mathcal{P}x.y.z\), where x is the chapter number, y is the section number within that chapter, and z is the problem number within that section. They will be set off as separate paragraphs from the rest of the text.
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Greenwood, P.E., Ward, L.M. (2016). Introduction. In: Stochastic Neuron Models. Mathematical Biosciences Institute Lecture Series(), vol 1.5. Springer, Cham. https://doi.org/10.1007/978-3-319-26911-5_1
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DOI: https://doi.org/10.1007/978-3-319-26911-5_1
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