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neuroConstruct and NeuroML related publications

Core publications

Padraig Gleeson, Volker Steuber, R. Angus Silver

neuroConstruct: A Tool for Modeling Networks of Neurons in 3D Space, Neuron, Volume 54, Issue 2, 19 April 2007, Pages 219-235.

PubMed Open access download

 

The main neuroConstruct paper. An introduction to all of the key functionality, including some network examples.

Please cite this paper if you use neuroConstruct in your research.

Padraig Gleeson, Volker Steuber, R. Angus Silver

Using neuroConstruct to Develop and Modify Biologically Detailed 3D Neuronal Network Models in Health and Disease. In Computational Neuroscience in Epilepsy, 2008, I. Soltesz, and K. Staley, eds. (Elsevier).

Elsevier

 

A chapter in a book outlining the various modelling approached being used in epilepsy research. Attractive image on the book cover...

Sharon Crook, Padraig Gleeson, Fred Howell, Joe Svitak, R. Angus Silver

MorphML: Level 1 of the NeuroML Standards for Neuronal Morphology Data and Model Specification, Neuroinformatics 2007, Volume 5; Number 2, Pages 96-104

PubMed

 

The introductory paper to MorphML. Compares morphological representations from NEURON, GENESIS, Neurolucida and neuroConstruct to MorphML.

Robert C. Cannon, Marc-Oliver Gewaltig, Padraig Gleeson, Upinder S. Bhalla, Hugo Cornelis, Michael L. Hines, Fredrick W. Howell, Eilif Muller, Joel R. Stiles, Stefan Wils, Erik De Schutter

Interoperability of Neuroscience Modeling Software: Current Status and Future Directions. Neuroinformatics 2007, Volume 5, 127-138.

PubMed

 

A review of the current state of interoperability for modelling applications, resulting from a workshop at CNS 2006.

The original NeuroML paper

Nigel Goddard, Michael Hucka, Fred Howell, Hugo Cornelis, Kavita Shankar, David Beeman

Towards NeuroML: Model Description Methods for Collaborative Modelling in Neuroscience. Philos Trans R Soc Lond B Biol Sci 356, 1209-1228.

PubMed

 

The original NeuroML introductory paper. Although the language has evolved significantly since this paper (with a focus now on key elements which need to be transferred between neuroinformatics applications, as represented by MorphML, ChannelML and NeuroML, the latest version of which are available here) the key aims of NeuroML as outlined in this paper, including clarity, portability and modularity of neuronal model descriptions, remain the same.

Combined experimental and modelling investigations

Jason S. Rothman, Laurence Cathala, Volker Steuber, R. Angus Silver

Synaptic depression enables neuronal gain control. Nature 2009

Advance Online Publication

 

An experimental and modelling paper looking at the effects of short term plasticity on gain control. Used neuroConstruct to investigate a detailed layer 5 pyramidal cell model (Kole et al 2008) with dendritically distributed excitatory and inhibitory synaptic input.

Nathan W. Gouwens and Rachel I. Wilson

Signal Propagation in Drosophila Central Neurons. Journal of Neuroscience 2009

Pubmed

 

A paper investigating the electrical properties of Drosophila neurons which utilises realistic morphological reconstructions and electrophysiological recordings.