Computational neuroscience - Info and Reading Options

"Computational neuroscience" Table Of Contents:

• 1- Introduction to equation solving and parameter fitting / Gwendal LeMasson and Reinoud Maex
• 2- Modeling networks of signaling pathways / Upinder S. Bhalla
• 3- Modeling local and global calcium signals using reaction-diffusion equations / Gregory D. Smith
• 4- Monte Carlo methods for simulating realistic synaptic microphysiology using MCell / Joel R. Stiles and Thomas M. Bartol
• 5- Which formalism to use for modeling voltage-dependent conductances? / Alain Destexhe and John Huguenard
• 6- Accurate reconstruction of neuronal morphology / Dieter Jaeger
• 7- Modeling dendritic geometry and the development of nerve connections / Jaap van Pelt, Arjen van Ooyen, and Harry B.M. Uylings
• 8- Passive cable modeling : a practical introduction / Guy Major
• 9- Modeling simple and complex active neurons / Erik De Schutter and Volker Steuber
• 10- Realistic modeling of small neuronal circuits / Ronald L. Calabrese, Andrew A.V. Hill, and Stephen D. van Hooser
• 11- Modeling of large networks / Michael E. Hasselmo and Ajay Kapur
• 12- Modeling of interactions between neural networks and musculoskeletal systems / Örjan Ekeberg.

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