Artificial Intelligence Driven by a General Neural Simulation System (Genesis)

Bahman Zohuri and Masoud Moghaddam
Galaxy Advanced Engineering, San Mateo, CA, USA

Series: Neurology – Laboratory and Clinical Research Developments
BISAC: MED056000

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Edited by I Leslie Rubin, Robert J Geller, Abby Mutic, Benjamin A Gitterman, Nathan Mutic, Wayne Garfinkel, Claire D Coles, Kurt Martinuzzi, and Joav Merrick

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The last several years have seen a dramatic increase in the number of neurobiologists building or using computer-based models as a regular part of their efforts to understand how different neural systems function. As experimental data continue to amass, it is increasingly clear that detailed physiological and anatomical data alone are not enough to infer how neural circuits work. Experimentalists appear to be recognizing the need for the quantitative approach to explore the functional consequences of particular neuronal features that are provided by modeling. This combination of modeling and experimental work has led to the creation of the new discipline of computational neurosciences.

More than the use of models per se, the authors believe that computational neuroscience is most distinguished from classical neurobiology due to an explicit focus on how the nervous system computes. Thus, instead of obtaining experimental information about the structure of the nervous system for its own sake, a computational approach involves collecting the information most relevant to the advancement of functional understanding.

In our hands, models, especially those based on the detailed physiology and anatomy of the brain region in question, capture what is known about this region while also directing further experimental investigations. These same models can then provide an interpretation for the obtained data. Thus, the interaction between experiments and computer modeling is increasingly iterative and interdependent.

About the Authors

Preface

Acknowledgment

Chapter 1. Computational Neuroscience

Chapter 2. Compartmental Modeling

Chapter 3. Neural Modeling with GENESIS

Chapter 4. The Hodgkin-Huxley Model

Chapter 5. Cable and Compartment Models of Dendritic Trees

Chapter 6. Temporal Interactions Between Postsynaptic Potentials

Chapter 7. Ion Channels in Bursting Neurons

Chapter 8. Central Pattern Generators

Chapter 9. Dynamics of Cerebral Cortical Networks

Chapter 10. The Network Within: Signaling Pathways

Chapter 11. Constructing New Models

Chapter 12. Introduction to GENESIS Programming

Chapter 13. Simulating a Neuron Soma

Chapter 14. Adding Voltage-Activated Channels

Chapter 15. Adding Dendrites and Synapses

Chapter 16. Automating Cell Construction with the Cell Reader

Chapter 17. Building a Cell with Neurokit

Chapter 18. Constructing Neural Circuits and Networks

Chapter 19. Implementing Other Types of Channels

Chapter 20. Speeding Up GENESIS Simulations

Chapter 21. Large-Scale Simulation Using Parallel GENESIS

Chapter 22. Advanced XOSUS Techniques: Simulation Visualization

Appendix A. Acquiring and Installing GENESIS

Appendix B. GENESIS Script Listing

Appendix C. Additional Information on Hodgkin-Huxley Model and Mathematics

Appendix D. The Goldman-Hodgkin-Katz Equation

Appendix E. The Nernst Equation

Appendix F. The Cable Theory

Index

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