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Principles of Computational Modelling in Neuroscience

What are the principles of computational modeling in neuroscience?
‘Principles of Computational Modelling in Neuroscience sets a new standard of clarity and insight in explaining biophysical models of neurons. This provides a firm foundation for network models of brain function and brain development. I plan to use this textbook in my course on computational neurobiology.’
How do we analyse computational mod-Els of the nervous system?
Most attempts to analyse computational mod-els of the nervous system involve using the powerful computers now avail-able to find numerical solutions to the complex sets of equations needed to construct an appropriate model.
What should be included in a computational neuroscience text-book?
Finally, two chapters introduce topics which we believe should belong in a computational neuroscience text-book: modelling extracellular influences on brain circuits (Chapter 10) and modelling the experimental measurement process (Chapter 13) so that model output can be matched more closely to experimental data.
What is a compartmental model of neuronal morphology?
It starts with the construction of a compartmental model by representing quasi-isopotential sections of neurite (small pieces of dendrite, axon or soma) as compartments, which are simple geometric objects such as spheres or cylinders. It then presents approaches for using real neuronal morphology as the basis of the model.

What are the principles of computational modeling in neuroscience?