Computational Systems Neurobiology

1. Front Matter

   Pages i-viii

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2. Functional Genomics and Molecular Networks Gene Expression Regulations in Complex Diseases: Down Syndrome as a Case Study

   • Marie-Claude Potier, Isabelle Rivals

   Pages 1-22

3. Reconstructing Models from Proteomics Data

   • Lysimachos Zografos, Andrew J. Pocklington, J. Douglas Armstrong

   Pages 23-80

4. Using Chemical Kinetics to Model Neuronal Signalling Pathways

   • Lukas Endler, Melanie I. Stefan, Stuart J. Edelstein, Nicolas Le Novère

   Pages 81-117

5. Breakdown of Mass-Action Laws in Biochemical Computation

   • Fidel Santamaria, Gabriela Antunes, Erik De Schutter

   Pages 119-132

6. Spatial Organization and Diffusion in Neuronal Signaling

   • Sherry-Ann Brown, Raquell M. Holmes, Leslie M. Loew

   Pages 133-161

7. The Performance (and Limits) of Simple Neuron Models: Generalizations of the Leaky Integrate-and-Fire Model

   • Richard Naud, Wulfram Gerstner

   Pages 163-192

8. Multi-compartmental Models of Neurons

   • Upinder S. Bhalla

   Pages 193-225

9. Noise in Neurons and Other Constraints

   • A. Aldo Faisal

   Pages 227-257

10. Methodological Issues in Modelling at Multiple Levels of Description

    • Kevin Gurney, Mark Humphries

    Pages 259-281

11. Virtues, Pitfalls, and Methodology of Neuronal Network Modeling and Simulations on Supercomputers

    • Anders Lansner, Markus Diesmann

    Pages 283-315

12. Co-operative Populations of Neurons: Mean Field Models of Mesoscopic Brain Activity

    • David T. J. Liley, Brett L. Foster, Ingo Bojak

    Pages 317-364

13. Cellular Spacing: Analysis and Modelling of Retinal Mosaics

    • Stephen J. Eglen

    Pages 365-385

14. Measuring and Modeling Morphology: How Dendrites Take Shape

    • Todd A. Gillette, Giorgio A. Ascoli

    Pages 387-427

15. Axonal Growth and Targeting

    • Duncan Mortimer, Hugh D. Simpson, Geoffrey J. Goodhill

    Pages 429-458

16. Encoding Neuronal Models in SBML

    • Sarah M. Keating, Nicolas Le Novère

    Pages 459-488

17. NeuroML

    • Padraig Gleeson, Volker Steuber, R. Angus Silver, Sharon Crook

    Pages 489-517

18. XPPAUT

    • Bard Ermentrout

    Pages 519-531

19. NEST by Example: An Introduction to the Neural Simulation Tool NEST

    • Marc-Oliver Gewaltig, Abigail Morrison, Hans Ekkehard Plesser

    Pages 533-558

20. Back Matter

    Pages 559-570

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Computational neurosciences and systems biology are among the main domains of life science research where mathematical modeling made a difference. This book introduces the many different types of computational studies one can develop to study neuronal systems. It is aimed at undergraduate students starting their research in computational neurobiology or more senior researchers who would like, or need, to move towards computational approaches. Based on their specific project, the readers would then move to one of the more specialized excellent textbooks available in the field. The first part of the book deals with molecular systems biology. Functional genomics is introduced through examples of transcriptomics and proteomics studies of neurobiological interest. Quantitative modelling of biochemical systems is presented in homogeneous compartments and using spatial descriptions. A second part deals with the various approaches to model single neuron physiology, and naturally moves to neuronal networks. A division is focused on the development of neurons and neuronal systems and the book closes on a series of methodological chapters. From the molecules to the organ, thinking at the level of systems is transforming biology and its impact on society. This book will help the reader to hop on the train directly in the tank engine.

• computational neurobiology
• dynamical modeling
• networks
• neuron
• systems biology

From the book reviews:

“This is an excellent reference on mathematical neurobiology at the single level, multiple level, and biophysical level. … This is a good neural modeling book which brings to light ideas concerning Bayes Theorems and NeuroML ensembles. I highly recommend it.” (Joseph J. Grenier, Amazon.com, July, 2014)

• European Bioinformatics Institute, EMBL-Outstation-Hinxton, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom

  N. Le Novère

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