20 Years of Computational Neuroscience

20 Years of Computational Neuroscience edited by James M Bower.

Twenty years ago, the field of Computational Neuroscience was relatively new and many computer models were starting to be constructed of different structures and brain regions. This book seeks to answer the questions, what have we learned over the last twenty years using computational techniques? an...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Bower, James M. (Editor)
Format: eBook
Language:English
Published: New York, NY : Springer New York : Imprint: Springer, 2013.
Edition:1st ed. 2013.
Series:Springer Series in Computational Neuroscience,
Springer eBook Collection.
Subjects:
Neurosciences.
Neurobiology.
Neural networks (Computer science) .
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • Introduction: Origins and History of the Annual CNS meetings
  • A Pictorial History of the Early Days of Computational Neuroscience:  The CNS Meeting Posters
  • History of Neural Simulation Software
  • Learning from the past:  Approaches for Reproducibility in Computational Neuroscience
  • The Emergence of Community Models in Computational Neuroscience: The 40-year History of the Cerebellar Purkinje Cell
  • Calcium: the Answer to Life, the Universe, and Everything
  • The more we look, the more biological variation we see: How has and should this influence modeling of small networks?
  • 20 years of “noise”: Contributions of computational neuroscience to the exploration of the effect of background activity on central neurons
  • Still looking for the memories: molecules and synaptic plasticity
  • 20 years of the dynamics of memory: The long and winding road linking cellular mechanisms to behavior
  • Spatiotemporal coding in the olfactory system
  • 20 years of learning about vision: Questions answered, questions unanswered, and questions not yet asked
  • Reinforcement learning models then and now: from single cells to modern neuroimaging
  • Index.

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