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neuroConstruct: 3D biophysically detailed neural network modelling
| Publisher: |
University College London |
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| Downloads: |
1 |
| Software Type: |
Freeware, 0.00 |
| File Size: |
48.89M |
| OS: |
Windows All |
| Update Date: |
28 March, 2013 |
neuroConstruct is being developed in the Silver Lab in the Department of Neuroscience, Physiology and Pharmacology at UCL. neuroConstruct has been designed to simplify development of complex networks of biologically realistic neurons, i.e. models incorporating dendritic morphologies and realistic cell membrane conductances. It is implemented in Java and generates script files for the NEURON and GENESIS simulators, with support for other simulation platforms (including PSICS, MOOSE and PyNN) in advanced stages of development. It uses the latest NeuroML specifications, including MorphML, ChannelML and NetworkML.
Development of this software was made possible with funding from the Wellcome Trust, the Medical Research Council and the EU Synapse Project.
Some of the key features of neuroConstruct are:
* neuroConstruct can import morphology files in GENESIS, NEURON, Neurolucida, SWC and MorphML format for inclusion in single cell or network models, or more abstract cells can also be built manually.
* Creation of networks of conductance based neurons positioned in 3D
* Complex connectivity patterns between cell groups can be specified for the networks
* Simulation scripts can be generated for NEURON, GENESIS, MOOSE, PSICS and PyNN based simulators (note: not every project can be generated for every simulator)
* Biophysically realistic cellular mechanisms (synapses/channel mechanisms) can be imported from native script files (*.mod or *.g) or created from templates using ChannelML
* Automatic generation of code to record simulation data and visualisation/analysis of data in neuroConstruct
* Recorded simulation runs can be viewed and managed through the Simulation Browser interface
* A Python based scripting interface can be used to control model generation and execution, allowing multiple simulations to be run for cell and network model optimisation
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