Encyclopedia of Computational Neuroscience

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 "...

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Bibliographic Details
Other Authors: Jaeger, Dieter (Editor), Jung, Ranu (Editor)
Format: eBook
Language:English
Published: New York, NY Springer New York 2015, 2015
Edition:1st ed. 2015
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of 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