neuroConstruct projects based on published neuronal and network models
- CA1PyramidalCell
- DentateGyrus
- GranCellLayer
- GranuleCell
- MainenEtAl_PyramidalCell
- PurkinjeCell
- RothmanEtAl_KoleEtAl_PyrCell
- SolinasEtAl_GolgiCell
- Thalamocortical
- VervaekeEtAl-GJCompensate
- VervaekeEtAl-GolgiCellNetwork
Downloadable neuroConstruct projects based on published conductance based models. Some examples to illustrate the core functionality of neuroConstruct, as opposed to providing electrophysiologically accurate models can be found here.
Note: These models are currently being moved to a repository to allow open source, collaborative development of NeuroML models.
See the Open Source Brain website for full details.
CA1PyramidalCell
Project name: CA1PyramidalCell Conversion of CA1 cell from Migliore et al 2005: http://senselab.med.yale.edu/ModelDB/ShowModel.asp?model=55035. This model can currently be executed in NEURON, GENESIS, MOOSE and PSICS. Project last modified: Thursday August 23, 2012 |
Downloads*: |
DentateGyrus
Project name: DentateGyrus A recreation of the model Dentate Gyrus from: Santhakumar V, Aradi I, Soltesz I. Role of mossy fiber sprouting and mossy cell loss in hyperexcitability: a network model of the dentate gyrus incorporating cell types and axonal topography. J Neurophysiol. 2005. Based on model scripts obtained from: http://senselab.med.yale.edu/senselab/modeldb/ShowModel.asp?model=51781 Project last modified: Thursday November 24, 2011 |
Downloads*: |
GranCellLayer
Project name: GranCellLayer An extension in 3D of the Granule Cell Layer model from: Maex, R and De Schutter, E. Synchronization of Golgi and Granule Cell Firing in a Detailed Network Model of the Cerebellar Granule Cell Layer J Neurophysiol, Nov 1998; 80: 2521 - 2537. The default Simulation Configuration replicates the 1D 75 granule cell example from: http://www.tnb.ua.ac.be/models/network.shtml. Project last modified: Thursday August 23, 2012 |
Downloads*: |
GranuleCell
Project name: GranuleCell A project illustrating the behaviour of the Granule Cell model from: Maex, R and De Schutter, E. Synchronization of Golgi and Granule Cell Firing in a Detailed Network Model of the Cerebellar Granule Cell Layer J Neurophysiol, Nov 1998; 80: 2521 - 2537. Based on scripts obtained from: http://www.tnb.ua.ac.be/models/network.shtml. Project last modified: Thursday August 23, 2012 |
Downloads*: |
MainenEtAl_PyramidalCell
Project name: MainenEtAl_PyramidalCell Implementation of the Mainen et al. pyramidal cell model from: Mainen ZF, Joerges J, Huguenard JR, Sejnowski TJ (1995) A model of spike initiation in neocortical pyramidal neurons. Neuron 15:1427-39. This project is based on scripts obtained from: http://senselab.med.yale.edu/senselab/modeldb/ShowModel.asp?model=8210. Project last modified: Thursday August 23, 2012 |
Downloads*: |
PurkinjeCell
Project name: PurkinjeCell An initial implementation in NeuroML of the Purkinje Cell model from De Schutter, E. and Bower, J. M. (1994). Based on Arnd Roth el al's conversion of the original GENESIS code to NEURON. Note: conversion not fully complete. Press Validate for details. Also, there are long standing issues about getting GENESIS and NEURON behaviour of the Purkinje cell to match. Contact P. Gleeson or A. Roth for more details on current status of this model. Project last modified: Thursday August 23, 2012 |
Downloads*: |
RothmanEtAl_KoleEtAl_PyrCell
Project name: RothmanEtAl_KoleEtAl_PyrCell A project which was used in Rothman et al. "Synaptic depression enables neuronal gain control" Nature 2009 to demonstrate gain control in realistic cell models. Based on cell model from Kole et al. 2008 (obtained from http://senselab.med.yale.edu/modeldb/ShowModel.asp?model=114394). The main Simulation Configuration generates an example of the activity of the pyramidal cell receiving excitatory input from 400 cells (via a depressing synapse) and inhibitory input from 30 cells. To generate the graphs in the paper, the input frequencies were changed manually through the GUI and the firing frequencies of the pyramidal cell recorded (note that simulations of 2-10s were used to get these frequencies and the first ~500ms of the activity was ignored). Such a process for running multiple similar simulations can be facilitated by using the Python interface to control simulation generation and execution. See pythonnC/Ex5_MultiSimGenerate.py for an example. Project last modified: Thursday August 23, 2012 |
Downloads*: |
SolinasEtAl_GolgiCell
Project name: SolinasEtAl_GolgiCell Multicompartmental model of cerebellar Golgi cell from: Solinas S, Forti L, Cesana E, Mapelli J, De Schutter E, D'Angelo E. (2007) Computational reconstruction of pacemaking and intrinsic electroresponsiveness in cerebellar Golgi cells. Front Cell Neurosci. 2007;1:2. Based on implemetation in NEURON taken from: http://senselab.med.yale.edu/modeldb/ShowModel.asp?model=112685. Project last modified: Thursday August 23, 2012 |
Downloads*: |
Thalamocortical
Project name: Thalamocortical This is a project implementing cells from the thalamocortical network model of Traub et al 2005 in NeuroML. Based on the NEURON implementation from: http://senselab.med.yale.edu/ModelDB/ShowModel.asp?model=45539. Project last modified: Thursday August 23, 2012 |
Downloads*: |
VervaekeEtAl-GJCompensate
Project name: VervaekeEtAl-GJCompensate From: Gap junctions compensate for sublinear dendritic integration in an inhibitory network By: Vervaeke, Lorincz, Nusser and Silver., Science 2012 Project last modified: Thursday March 8, 2012 |
Downloads*: |
VervaekeEtAl-GolgiCellNetwork
Project name: VervaekeEtAl-GolgiCellNetwork Network of electrically coupled cerebellar Golgi cells, as described in Vervaeke et al. Rapid Desynchronization of an Electrically Coupled Interneuron Network with Sparse Excitatory Synaptic Input, Neuron 2010. The Golgi cell model is based on the abstract cell model in Solinas et al., Frontiers in Neuroscience 2007. Project last modified: Thursday August 23, 2012 |
Downloads*: |
* Note: neuroConstruct project downloads (most of which are included with the standard software distribution) can be loaded directly into neuroConstruct to generate cell and network scripts for NEURON, GENESIS, etc., but NeuroML downloads just consist of the core elements of the project (morphologies, channels, etc.) which have been exported in NeuroML format. The latter can be useful for testing NeuroML compliant applications. If no NeuroML download link is present, this usually indicates that the model is mainly implemented using channel/synapse mechanisms in a simulator's native language (e.g. mod files) which have not fully been converted to ChannelML yet.