Abstract
This chapter introduces the concept of modeling. In the past chapters we discussed the analysis of data from various sources. Here, we build single neurons from scratch (in silico) to understand how they generate spiking behavior on the basis of biophysical properties. Specifically, we create them as objects in order to cover the subject of object-oriented programming (OOP) and discuss the virtues of OOP and simulations in general. We then simulate current injections into these model neurons in order to understand basic input–output relationships. Finally, we use curve-fitting techniques to model the spiking responses of these simulated neurons and discuss how to assess the goodness of fit between model and the data using standard metrics like root mean squared error or r squared.
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