By Topic

Neurobiology of Neural Networks

Cover Image Copyright Year: 2003
Author(s): Daniel Gardner
Publisher: MIT Press
Content Type : Books & eBooks
Topics: Bioengineering
  • Print

Abstract

This timely overview and synthesis of recent work in both artificial neural networks and neurobiology seeks to examine neurobiological data from a network perspective and to encourage neuroscientists to participate in constructing the next generation of neural networks. Individual chapters were commissioned from selected authors to bridge the gap between present neural network models and the needs of neurophysiologists who are trying to use these models as part of their research on how the brain works.Daniel Gardner is Professor of Physiology and Biophysics at Cornell University Medical College.Contents: Introduction: Toward Neural Neural Networks, Daniel Gardner. Two Principles of Brain Organization: A Challenge for Artificial Neural Networks, Charles F. Stevens. Static Determinants of Synaptic Strength, Daniel Gardner. Learning Rules From Neurobiology, Douglas A. Baxter and John H. Byrne. Realistic Network Models of Distributed Processing in the Leech, Shawn R. Lockery and Terrence J. Sejnowski. Neural and Peripheral Dynamics as Determinants of Patterned Motor Behavior, Hillel J. Chiel and Randall D. Beer. Dynamic Neural Network Models of Sensorimotor Behavior, Eberhard E. Fetz.

  •   Click to expandTable of Contents

    • Full text access may be available. Click article title to sign in or learn about subscription options.

      Front Matter

      Page(s): i - xiii
      Copyright Year: 2003

      MIT Press eBook Chapters

      This chapter contains sections titled: Half Title, Title, Copyright, Contents, Series Foreword, Contributors, Preface View full abstract»

    • Full text access may be available. Click article title to sign in or learn about subscription options.

      Introduction

      Page(s): 1 - 11
      Copyright Year: 2003

      MIT Press eBook Chapters

      This chapter contains sections titled: Neuron And Network, Toward A New Generation Of Neural Networks, Parents Of The Third Generation, Neural Networks: The Excitement Persists, The Neurobiology Of Neural Networks And The Third Generation, Beyond The Neurobiology Of Neural Networks, Acknowledgment View full abstract»

    • Full text access may be available. Click article title to sign in or learn about subscription options.

      Two Principles of Brain Organization

      Page(s): 13 - 20
      Copyright Year: 2003

      MIT Press eBook Chapters

      This chapter contains sections titled: Scaling Properties Of Cortex, Classes 0F Neural Networks, Conclusions, Acknowledgment View full abstract»

    • Full text access may be available. Click article title to sign in or learn about subscription options.

      Static Determinants of Synaptic Strength

      Page(s): 21 - 70
      Copyright Year: 2003

      MIT Press eBook Chapters

      This chapter contains sections titled: The Neurophysiology Of Neural Network Models, The Neurobiology Of A Biological Neural Network, Buccal Ganglia Synaptic Strengths Differ Both Statically And Dynamically, Cell And Network Properties Of The Buccal Ganglia Transcend Simplifying Assumptions Of Network Models, Backpropagation Imposes A Requirement For Retrograde Information Transfer, Buccal Ganglia Synaptic Strengths Are Specified By Postsynaptic Neurons, Postsynaptic Neurons Specify Presynaptic Quantal Release, Aplysia Neurobiological. Mechanisms Consistent With Retrosynaptic Information Transfer, Static And Dynamic Retrosynaptic Plasticity In Neurobiology, Retrosynaptic Mechanisms For Network Learning Rules, Acknowledgment View full abstract»

    • Full text access may be available. Click article title to sign in or learn about subscription options.

      Learning Rules from Neurobiology

      Page(s): 71 - 105
      Copyright Year: 2003

      MIT Press eBook Chapters

      This chapter contains sections titled: Nonassociative Synaptic Modifications, Associative Synaptic Modifications, Conclusions, Acknowledgments View full abstract»

    • Full text access may be available. Click article title to sign in or learn about subscription options.

      Realistic Network Models of Distributed Processing in the Leech

      Page(s): 107 - 135
      Copyright Year: 2003

      MIT Press eBook Chapters

      This chapter contains sections titled: Modeling Overview, A Case Study: The Leech Local Bending Reflex, Conclusion, Acknowledgment View full abstract»

    • Full text access may be available. Click article title to sign in or learn about subscription options.

      Neural and Peripheral Dynamics as Determinants of Patterned Motor Behavior

      Page(s): 137 - 164
      Copyright Year: 2003

      MIT Press eBook Chapters

      This chapter contains sections titled: Neural Network Dynamics, Peripheral Dynamics, Neural/Peripheral Interactions, A Biologically Inspired Controller For Hexapod Locomotion, Conclusions, Acknowledgments View full abstract»

    • Full text access may be available. Click article title to sign in or learn about subscription options.

      Dynamic Neural Network Models of Sensorimotor Behavior

      Page(s): 165 - 190
      Copyright Year: 2003

      MIT Press eBook Chapters

      This chapter contains sections titled: Applications, Future Directions, Conclusions, Acknowledgments View full abstract»

    • Full text access may be available. Click article title to sign in or learn about subscription options.

      References

      Page(s): 191 - 218
      Copyright Year: 2003

      MIT Press eBook Chapters

      This timely overview and synthesis of recent work in both artificial neural networks and neurobiology seeks to examine neurobiological data from a network perspective and to encourage neuroscientists to participate in constructing the next generation of neural networks. Individual chapters were commissioned from selected authors to bridge the gap between present neural network models and the needs of neurophysiologists who are trying to use these models as part of their research on how the brain works.Daniel Gardner is Professor of Physiology and Biophysics at Cornell University Medical College.Contents: Introduction: Toward Neural Neural Networks, Daniel Gardner. Two Principles of Brain Organization: A Challenge for Artificial Neural Networks, Charles F. Stevens. Static Determinants of Synaptic Strength, Daniel Gardner. Learning Rules From Neurobiology, Douglas A. Baxter and John H. Byrne. Realistic Network Models of Distributed Processing in the Leech, Shawn R. Lockery and Terrence J. Sejnowski. Neural and Peripheral Dynamics as Determinants of Patterned Motor Behavior, Hillel J. Chiel and Randall D. Beer. Dynamic Neural Network Models of Sensorimotor Behavior, Eberhard E. Fetz. View full abstract»

    • Full text access may be available. Click article title to sign in or learn about subscription options.

      Index

      Page(s): 219 - 227
      Copyright Year: 2003

      MIT Press eBook Chapters

      This timely overview and synthesis of recent work in both artificial neural networks and neurobiology seeks to examine neurobiological data from a network perspective and to encourage neuroscientists to participate in constructing the next generation of neural networks. Individual chapters were commissioned from selected authors to bridge the gap between present neural network models and the needs of neurophysiologists who are trying to use these models as part of their research on how the brain works.Daniel Gardner is Professor of Physiology and Biophysics at Cornell University Medical College.Contents: Introduction: Toward Neural Neural Networks, Daniel Gardner. Two Principles of Brain Organization: A Challenge for Artificial Neural Networks, Charles F. Stevens. Static Determinants of Synaptic Strength, Daniel Gardner. Learning Rules From Neurobiology, Douglas A. Baxter and John H. Byrne. Realistic Network Models of Distributed Processing in the Leech, Shawn R. Lockery and Terrence J. Sejnowski. Neural and Peripheral Dynamics as Determinants of Patterned Motor Behavior, Hillel J. Chiel and Randall D. Beer. Dynamic Neural Network Models of Sensorimotor Behavior, Eberhard E. Fetz. View full abstract»