NEURON
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== Usage Overview == | == Usage Overview == | ||
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| + | The most important strategy is to offer users what might be called "natural syntax," which allows them to specify model properties in familiar idioms, rather than having to cast kinetic schemes or differential equations in the form of statements in C or some other generic programming language. Perhaps the most prominent example of natural syntax in NEURON is the notion of a section, which is a continuous unbranched cable (directly analogous to an unbranched neurite). Sections can be connected together to form branched trees, and are endowed with properties that can vary continuously with position along their lengths. Sections let investigators represent neuronal anatomy without having to wrestle with the cable equation. They also easily lend themselves to manipulation by graphical tools, such as the CellBuilder, for building and managing models. | ||
== Dependencies == | == Dependencies == | ||
Latest revision as of 10:59, 25 April 2012
Contents |
- Web site: http://www.neuron.yale.edu/neuron/
- Described version: 7.1
- Licensing: e.g. GPL 2
- User documentation: http://www.neuron.yale.edu/neuron/
- Download: link
- Source code: http://www.neuron.yale.edu/neuron/
Authors/Maintainers
- Ted Hines, N. Carnevale
Summary
NEURON is a simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well-suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties
Features
NEURON's computational engine employs special algorithms that achieve high efficiency by exploiting the structure of the equations that describe neuronal properties. It has functions that are tailored for conveniently controlling simulations, and presenting the results of real neurophysiological problems graphically in ways that are quickly and intuitively grasped. Instead of forcing users to reformulate their conceptual models to fit the requirements of a general purpose simulator, NEURON is designed to let them deal directly with familiar neuroscience concepts. Consequently, users can think in terms of the biophysical properties of membrane and cytoplasm, the branched architecture of neurons, and the effects of synaptic communication between cells.
- Domain-specific programming and configuration language (HOC)
- Parallel processing support through MPI
- Modular architecture using DL libraries to implement ionic equation kinetics
- High resolution differential equation solver (CVODE)
Architectural/Functional Overview
- Separates biology from purely computational concerns
- Integrator-independent model specification
- Efficient spatial and temporal discretization
- Graphical user interface
- User-extendable library of biophysical mechanisms
- Customizable initialization and simulation flow control
Usage Overview
The most important strategy is to offer users what might be called "natural syntax," which allows them to specify model properties in familiar idioms, rather than having to cast kinetic schemes or differential equations in the form of statements in C or some other generic programming language. Perhaps the most prominent example of natural syntax in NEURON is the notion of a section, which is a continuous unbranched cable (directly analogous to an unbranched neurite). Sections can be connected together to form branched trees, and are endowed with properties that can vary continuously with position along their lengths. Sections let investigators represent neuronal anatomy without having to wrestle with the cable equation. They also easily lend themselves to manipulation by graphical tools, such as the CellBuilder, for building and managing models.
Dependencies
- Interviews Graphics Library (bundled in source)
HP-SEE Applications
Resource Centers
Usage by Other Projects and Communities
Recommendations for Configuration and Usage
Please change MPI environment to openMPI before compiling.
Install neuron from source following the instructions in http://www.neuron.yale.edu/neuron/download/compile_linux
Configure with --with-nrnpara option
