By FENG. JIANFENG, Jianfeng Feng
Computational Neuroscience: A finished strategy presents a unified remedy of the mathematical conception of the anxious process and offers concrete examples demonstrating how computational strategies can light up tricky neuroscience difficulties. In chapters contributed via best researchers, the ebook introduces the fundamental mathematical thoughts, then examines modeling in any respect degrees, from single-channel and unmarried neuron modeling to neuronal networks and system-level modeling. The emphasis is on types with shut ties to experimental observations and knowledge, and the authors evaluation software of the types to platforms similar to olfactory bulbs, fly imaginative and prescient, and sensorymotor platforms.
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Extra info for Computational Neuroscience: A Comprehensive Approach
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And Brown, D. (2000). A reduced compartmental model of the mitral cell for use in network models of the olfactory bulb. Brain Research Bulletin 51: 393-399. , and Abbott, L. (2002). Theoretical Neuroscience. MIT press: Cambridge, Massachusetts. , Vanden-Eijnden, E. (2002). String method for the study of rare events. Phys. Rev. B 66: 052301. , and Kleinfeld, D. (2001). Travelling electrical waves in cortex: insights from phase dynamics and speculation on a computational role. Neuron 29: 33-44.
Finally, at the lowest level of detail, both ions and solvent are treated implicitly, as mean fields, and the channel itself may be either atomic detail or simplified as well. At this level of approximation it is computationally easy to calculate macroscopic properties, but it is challenging to obtain accurate results. Recently, simulations have also begun to study interactions of toxins and other small molecules with ion channels, providing an additional possible link with experimental work. I conclude with a review of selected recent applications to a number of model ion channels and give a brief outlook of how simulations might contribute in the future to a better understanding of how ion channels work.
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