neuroConstruct and NeuroML related publications
Core publications
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neuroConstruct: A Tool for Modeling Networks of Neurons in 3D Space, Neuron, Volume 54, Issue 2, 19 April 2007, Pages 219-235. Padraig Gleeson, Volker Steuber, R. Angus Silver |
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. |
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NeuroML: A Language for Describing Data Driven Models of Neurons and Networks with a High Degree of Biological Detail, PLoS Comput Biol 6(6): e1000815 Padraig Gleeson, Sharon Crook, Robert C. Cannon, Michael L. Hines, Guy O. Billings, Matteo Farinella, Thomas M. Morse, Andrew P. Davison, Subhasis Ray, Upinder S. Bhalla, Simon R. Barnes, Yoana D. Dimitrova, R. Angus Silver |
The main NeuroML paper. Describes in detail the structure of version 1.x (Levels 1-3, MorphML, ChannelML, NetworkML), includes a detailed discussion of the elements present at each level along with example NeuroML code (see the supporting text of the paper), outlines current simulator support, and presents a number of new cell and network models which have recently been converted to the format. Please cite this paper if you use NeuroML in your research. |
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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). Padraig Gleeson, Volker Steuber, R. Angus Silver |
A chapter in a book outlining the various modelling approached being used in epilepsy research. Attractive image on the book cover... |
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MorphML: Level 1 of the NeuroML Standards for Neuronal Morphology Data and Model Specification, Neuroinformatics 2007, Volume 5; Number 2, Pages 96-104 Sharon Crook, Padraig Gleeson, Fred Howell, Joe Svitak, R. Angus Silver |
The introductory paper to MorphML. Compares morphological representations from NEURON, GENESIS, Neurolucida and neuroConstruct to MorphML. |
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Interoperability of Neuroscience Modeling Software: Current Status and Future Directions, Neuroinformatics 2007, Volume 5, 127-138. 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 |
A review of the current state of interoperability for modelling applications, resulting from a workshop at CNS 2006. |
The original NeuroML paper
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Towards NeuroML: Model Description Methods for Collaborative Modelling in Neuroscience, Philos Trans R Soc Lond B Biol Sci 356, 1209-1228. Nigel Goddard, Michael Hucka, Fred Howell, Hugo Cornelis, Kavita Shankar, David Beeman |
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, see Gleeson et al. 2010 above for details) 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
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Synaptic depression enables neuronal gain control, Nature 2009 Jason S. Rothman, Laurence Cathala, Volker Steuber, R. Angus Silver |
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. |
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Signal Propagation in Drosophila Central Neurons, Journal of Neuroscience 2009 Nathan W. Gouwens and Rachel I. Wilson |
A paper investigating the electrical properties of Drosophila neurons which utilises realistic morphological reconstructions and electrophysiological recordings. |