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Principles of Computational Modelling in Neuroscience Hardcover – 30 Jun 2011


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Product details

  • Hardcover: 404 pages
  • Publisher: Cambridge University Press; 1 edition (30 Jun. 2011)
  • Language: English
  • ISBN-10: 0521877954
  • ISBN-13: 978-0521877954
  • Product Dimensions: 18.9 x 2.3 x 24.6 cm
  • Average Customer Review: Be the first to review this item
  • Amazon Bestsellers Rank: 282,584 in Books (See Top 100 in Books)
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Review

'Here at last is a book that is aware of my problem, as an experimental neuroscientist, in understanding the maths … I expect it to be as mind expanding as my involvement with its authors was over the years. I only wish I had had the whole book sooner - then my students and post-docs would have been able to understand what I was trying to say and been able to derive the critical tests of the ideas that only the rigor of the mathematical formulation of them could have generated.' Gordon W. Arbuthnott, Okinawa Institute of Science and Technology

'This is a wonderful, clear and compelling text on mathematically-minded computational modelling in neuroscience. It is beautifully aimed at those engaged in capturing quantitatively, and thus simulating, complex neural phenomena at multiple spatial and temporal scales, from intracellular calcium dynamics and stochastic ion channels, through compartmental modelling, all the way to aspects of development. It takes particular care to define the processes, potential outputs and even some pitfalls of modelling; and can be recommended for containing the key lessons and pointers for people seeking to build their own computational models. By eschewing issues of coding and information processing, it largely hews to concrete biological data, and it nicely avoids sacrificing depth for breadth. It is very suitably pitched as a Master's level text, and its two appendices, on mathematical methods and software resources, will rapidly become dog-eared.' Peter Dayan, University College London

'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.' Terrence Sejnowski, Salk Institute for Biological Studies and University of California, San Diego

Book Description

This book is for neuroscientists at all levels and for people from the informational and physical sciences who want to develop computational models of the neuron and neural circuits. It presents the principles of computational neuroscience in a clear and coherent manner, and addresses practical issues that arise in modelling projects.

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Amazon.com: 5.0 out of 5 stars 1 reviews
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5.0 out of 5 starsA comprehensive treatment of computational modeling in neuroscience
on 18 October 2011 - Published on Amazon.com
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