Encyclopedia of Computational Neuroscience

2015 Edition
| Editors: Dieter Jaeger, Ranu Jung

Neuronal Model Optimization: Overview

  • Astrid A. Prinz
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-6675-8_753



Neuronal Model Parameter Optimization is the process of adjusting the parameters of a computational model of a neuron or neuronal network in order to achieve model activity that mimics that of the living neuron or network being modeled.

Detailed Description

This section contains entries that explain the need for neuron and network model parameter optimization, discuss various optimization methods, describe existing software tools for optimization and visualization of the model databases that result from some of the optimization methods, and discuss related concepts that have emerged from model optimization and exploration efforts over the last few years.

Why do Neuronal Model Parameters Need to Be Optimized?

Computational models of neurons and neuronal circuits are important investigative tools that allow the study of neuronal signaling and information processing mechanisms that would not be experimentally accessible. However, constructing a...

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of BiologyEmory UniversityAtlantaUSA