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Encyclopedia of Computational Neuroscience
Author
Title
Encyclopedia of Computational Neuroscience [electronic resource] / edited by Dieter Jaeger, Ranu Jung.
ISBN
9781461466758
Publication
New York, NY : Springer New York : Imprint: Springer, 2015.
Physical Description
LXIII, 3,180 p. 1,109 illus., 769 illus. in color. eReference : online resource.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
The annual Computational Neuroscience Meeting (CNS) began in 1990 as a small workshop called Analysis and Modeling of Neural Systems. The goal of the workshop was to explore the boundary between neuroscience and computation. Riding on the success of several seminal papers, physicists had made "Neural Networks" fashionable, and soon the quantitative methods used in these abstract model networks started permeating the methods and ideas of experimental neuroscientists. Although experimental neurophysiological approaches provided many advances, it became increasingly evident that mathematical and computational techniques would be required to achieve a comprehensive and quantitative understanding of neural system function. “Computational Neuroscience” emerged to complement experimental neurophysiology. The Encyclopedia of Computational Neuroscience, published in conjunction with the Organization for Computational Neuroscience, will be an extensive reference work consultable by both researchers and graduate level students. It will be a dynamic, living reference, updatable and containing linkouts and multimedia content whenever relevant.
Other formats
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
April 09, 2015
Contents
Information Theory
Vestibular System
Brute Force Methods in Computational Neuroscience
Low Frequency Oscillations (Anesthesia and Sleep)
Invertebrate Pattern Generation
Gamma and Theta Oscillations, Hippocampus
Cable Theory
Vertebrate Pattern Generation
Neural Population Models and Cortical Field Theory
Basal Ganglia
Brain Imaging
Modeling Software Tools
Model Reproducibility
Auditory Sensing Systems
Neuromorphic Engineering
Ion Channel Types and Modeling
Compartmental Modeling
Dynamical Systems
Biochemical Signaling Pathways and Diffusion
Modeling of Disease
Molecular Level
Peripheral Nerve Interfaces
Brain Scale Networks
Brainstem Processing
Phase Response Curves
Computational Neuroanatomy
Multistability in Neurodynamics
Decision Making
Invertebrate Sensory Systems
Synaptic Dynamics
Deep Brain Stimulation (Models, Theory, Techniques)
Motor Neuron Models
Somatosensory System
Spike Train Analysis
Spectral Methods in Neural Data Analysis
Bayesian Approaches in Computational Neuroscience
Cerebellum
Databases in Computational Neuroscience
Dynamics of Disease States
LFP Analysis
Brain Machine Interface
Cortex
Spinal Interfaces
Olfaction
Neuromodulation
Spinal Cord
Retinal/Visual Interfaces (Models, Theory, Techniques)
Learning Rules
Visual System
Spiking Network Models and Theory
Neuromechanics.
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