Journal articles and book chapters

  • Pouzat C., Davison A. and Hinsen K. (2015) La recherche reproductible : une communication scientifique explicite. Statistique et société 3: 35--38 [BibTeX]
  • Muller, E., Bednar, J.A., Diesmann, M., Gewaltig, M.-O., Hines, M. and Davison, A.P. (2015) Python in Neuroscience. Frontiers in Neuroinformatics 9: doi:10.3389/fninf.2015.00011 [BibTeX]
  • Davison A.P., Mattioni M., Samarkanov D. and Teleńczuk B. (2014) Sumatra: A Toolkit for Reproducible Research. In: Implementing Reproducible Research, edited by V. Stodden and F. Leisch and R.D. Peng, Chapman & Hall/CRC. [BibTeX] [Full text] [Book]
  • Vella M., Cannon R.C., Crook S., Davison A.P., Ganapathy G., Robinson H.P.C., Silver R.A. and Gleeson P. (2014) libNeuroML and PyLEMS: using Python to combine procedural and declarative modelling approaches in computational neuroscience. Frontiers in Neuroinformatics 8:38: doi:10.3389/fninf.2014.00038 [BibTeX] [Full text]
  • Djurfeldt M., Davison A.P. and Eppler J.M. (2014) Efficient generation of connectivity in neuronal networks from simulator-independent descriptions. Frontiers in Neuroinformatics 8:43: doi:10.3389/fninf.2014.00043 [BibTeX] [Full text]
  • Garcia S., Guarino D., Jaillet F., Jennings T.R., Pröpper R., Rautenberg P.L., Rodgers C., Sobolev A., Wachtler T., Yger P. and Davison A.P. (2014) Neo: an object model for handling electrophysiology data in multiple formats. Frontiers in Neuroinformatics 8:10: doi:10.3389/fninf.2014.00010 [BibTeX] [Full text]
  • Antolík J. and Davison A.P. (2013) Integrated workflows for spiking neuronal network simulations. Frontiers in Neuroinformatics 7:34: doi:10.3389/fninf.2013.00034 [BibTeX] [Full text]
  • Davison A.P. (2013) NineML. In: Encyclopedia of Computational Neuroscience: SpringerReference, edited by Jaeger D. and Jung R., Springer-Verlag. doi:10.1007/SpringerReference_348440 [BibTeX] [Full text]
  • Davison A.P. (2013) PyNN: a Python API for Neural Network Modelling. In: Encyclopedia of Computational Neuroscience: SpringerReference, edited by D. Jaeger and R. Jung, Springer-Verlag. [BibTeX] [Full text]
  • Crook S.M, Davison A.P. and Plesser H.E. (2013) Learning from the past: approaches for reproducibility in computational neuroscience. In: 20 Years of Computational Neuroscience, edited by J.M. Bower, Springer. [BibTeX]
  • Crook S.M., Bednar J.A., Berger S., Cannon R., Davison A.P., Djurfeldt M., Eppler J., Kriener B., Furber S., Graham B., Plesser H.E., Schwabe L., Smith L., Steuber V. and van Albada S. (2012) Creating, documenting and sharing network models.. Network: Computation in Neural Systems 23: 131--149 doi:10.3109/0954898X.2012.722743 [BibTeX] [Full text] [Preprint]
  • Davison A.P. (2012) Collaborative modelling: the future of computational neuroscience?. Network: Computation in Neural Systems 23: 157--166 doi:10.3109/0954898X.2012.718482 [BibTeX] [Full text] [Preprint]
  • Davison A.P. (2012) Automated capture of experiment context for easier reproducibility in computational research. Computing in Science and Engineering 14: 48--56 [BibTeX] [Full text] [Preprint]
  • Brüderle D., Petrovici M.A., Vogginger B., Ehrlich M., Pfeil T., Millner S., Grübl A., Wendt K., Müller E., Schwartz M.O., Husmann de Oliveira D., Jeltsch S., Fieres J., Schilling M., Müller P., Breitwieser O., Petkov V., Muller L., Davison A.P., Krishnamurthy P., Kremkow J., Lundqvist M., Muller E., Partzsch J., Scholze S., Zühl L., Mayr C., Destexhe A., Diesmann M., Potjans T.C., Lansner A., Schüffny R., Schemmel J. and Meier K. (2011) A Comprehensive Workflow for General-Purpose Neural Modeling with Highly Configurable Neuromorphic Hardware Systems. Biological Cybernetics 104: 263--296 [BibTeX] [Full text] [Preprint]
  • Gleeson P., Crook S., Cannon R.C., Hines M.L., Billings, G.O., Farinella M., Morse T.M., Davison A.P., Ray S., Bhalla U.S., Barnes S.R., Dimitrova Y.D., Silver and R.A. (2010) NeuroML: A language for describing data driven models of neurons and networks with a high degree of biological detail. PLoS Computational Biology 6: e1000815 doi:10.1371/journal.pcbi.1000815 [BibTeX] [Full text]
  • Marre O., Yger P., Davison A.P. and Frégnac Y. (2009) Reliable recall of spontaneous activity patterns in cortical networks. The Journal of Neuroscience 29: 14596--14606 [BibTeX]
  • Bruederle D., Muller E., Davison A., Muller E., Schemmel J. and Meier K. (2009) Establishing a Novel Modeling Tool: A Python-based Interface for a Neuromorphic Hardware System. Frontiers in Neuroinformatics 3:17: doi:10.3389/neuro.11.017.2009 [BibTeX] [Full text]
  • Davison A.P., Brüderle D., Eppler J.M., Kremkow, J., Muller E., Pecevski D.A., Perrinet L. and Yger P. (2009) PyNN: a common interface for neuronal network simulators. Frontiers in Neuroinformatics 2:11: doi:10.3389/neuro.11.011.2008 [BibTeX] [Full text]
  • Hines M.L., Davison A.P. and Muller E. (2009) NEURON and Python. Frontiers in Neuroinformatics 3:1: doi:10.3389/neuro.11.001.2009 [BibTeX] [Full text]
  • R. Brette and 21 others (2007) Simulation of networks of spiking neurons: A review of tools and strategies. Journal of Computational Neuroscience 23: 349--398 [BibTeX] [Preprint] [Get the model from ModelDB]
  • Frégnac Y., Rudolph M., Davison A.P. and Destexhe A. (2007) Complexity in Neuronal Networks. In: Biological Networks, edited by François Képès, World Scientific. [BibTeX] [Book]
  • Davison A.P. and Frégnac Y. (2006) Learning crossmodal spatial transformations through spike-timing-dependent plasticity. The Journal of Neuroscience 26: 5604--5615 [BibTeX] [Get the model from ModelDB]
  • Badoual M., Zou Q., Davison A.P., Rudolph M., Bal T., Frégnac Y. and Destexhe A. (2006) Biophysical and phenomenological models of multiple spike interactions in spike-timing dependent plasticity. International Journal of Neural Systems 16: 79--97 [BibTeX] [Get the model from ModelDB]
  • Davison A.P. (2004) Biologically-detailed network modelling. In: Computational Neuroscience: A Comprehensive Approach, edited by J. Feng, Chapman and Hall/CRC Press. [BibTeX]
  • Davison A.P., Feng J. and Brown D. (2003) Dendrodendritic inhibition and simulated odor responses in a detailed olfactory bulb network model. Journal of Neurophysiology 90: 1921--1935 doi:10.1152/jn.00623.2002 [BibTeX] [Full text] [Get the model from ModelDB]
  • Davison A.P. and Shepherd G.M. (2002) Olfactory Bulb. In: The Handbook of Brain Theory and Neural Networks, 2nd Edn, edited by M. Arbib, The MIT Press. [BibTeX]
  • Davison A.P., Morse T.M., Migliore M., Marenco L., Shepherd G.M. and Hines M.L. (2002) ModelDB: A Resource for Neuronal and Network Modeling. In: Neuroscience Databases: A Practical Guide, edited by R. Kötter, Kluwer Academic Publishers. [BibTeX]
  • Davison A.P. (2001) Mathematical modelling of information processing in the olfactory bulb. Ph.D. thesis, University of Cambridge. [BibTeX] [Full text]
  • Davison A.P., Feng J. and Brown D. (2000) A reduced compartmental model of the mitral cell for use in network models of the olfactory bulb. Brain Research Bulletin 51: 393--399 doi:10.1016/S0361-9230(99)00256-7 [BibTeX] [Get the model from ModelDB]

Conference presentations

  • Antolik J. and Davison A.P. (2013) Mozaik: a framework for model construction, simulation, data analysis and visualization for large-scale spiking neural circuit models. Front. Neuroinform. Conference Abstract doi:10.3389/conf.fninf.2013.09.00018
    Neuroinformatics 2013, Stockholm, Sweden, August. [Full text] [Proceedings]
  • Davison A.P., Djurfeldt M., Eppler J.M., Gleeson P., Hull M. and Muller E.B. (2013) An integration layer for neural simulation: PyNN in the software forest. Front. Neuroinform. Conference Abstract doi:10.3389/conf.fninf.2013.09.00020
    Neuroinformatics 2013, Stockholm, Sweden, August. [Full text] [Poster] [Proceedings]
  • Davison A.P. (2013) Sumatra: a system for reproducible research.
    Workshop on Software Infrastructure for Reproducibility in Science, NYU Poly, New York, USA, May. [Slides]
  • Davison A.P. (2013) PyNN: a simulator-independent platform for large-scale data-driven neuronal simulations.
    Large-scale neuronal simulations - science, languages and platforms, Cosyne workshops, Snowbird, Utah, USA, March. [Slides]
  • Davison A.P. (2013) Provenance tracking for complex data analysis workflows in neuroscience.
    10th Göttingen Meeting of the German Neuroscience Society, Göttingen, Germany, March.
  • Davison A.P. (2012) Sumatra: a toolkit for provenance capture and reuse.
    ICERM workshop on Reproducibility in Computational and Experimental Mathematics, Providence, RI, USA, December. [Slides]
  • Eppler J.M., Djurfeldt M., Muller E., Diesmann M. and Davison A.P. (2012) Combining simulator independent network descriptions with run-time interoperability based on PyNN and MUSIC.
    Neuroinformatics 2012, Munich, Germany, September.
  • Denker M., Davison A.P., Diesmann M. and Grün S. (2012) Implementing Workflow Strategies to Handle the Analysis of Complex Electrophysiological Data Sets.
    Neuroinformatics 2012, Munich, Germany, September.
  • Guarino D. and Davison A.P. (2012) On running neural network simulations inside databases.
    FENS, Barcelona, Spain, July.
  • Le Franc Y., Davison A.P., Gleeson P., Imam F.T., Kriener B., Larson S.D., Ray S., Schwabe L., Hill S. and De Schutter E. (2012) Computational Neuroscience Ontology: a new tool to provide semantic meaning to your models. BMC Neuroscience 13(Suppl 1): P149. doi:10.1186/1471-2202-13-S1-P149
    CNS*2012, Decatur, GA, USA, July. [Proceedings]
  • Denker M., Davison A.P., Diesmann M. and Gruen S. (2011) How collaborative projects that involve complicated electrophysiological data sets profit from workflow design. Front. Neuroinform. Conference Abstract
    Neuroinformatics 2011, Boston, MA, USA, September. [Proceedings]
  • Davison A.P. (2011) Collaborative and reproducible simulation and data analysis with Sumatra. Front. Neuroinform. Conference Abstract
    Neuroinformatics 2011, Boston, MA, USA, September. [Proceedings]
  • Gorchetchnikov A., Cannon R., Clewley R., Cornelis H., Davison A.P., De Schutter E., Djurfeldt M., Gleeson P., Hill S., Hines M., Kriener B., Le Franc Y., Lo C.-C., Morrison A., Muller E., Plesser H.E., Raikov I., Ray S., Schwabe L. and Szatmary B. (2011) NineML: declarative, mathematically-explicit descriptions of spiking neuronal networks. Front. Neuroinform. Conference Abstract doi:10.3389/conf.fninf.2011.08.00098
    Neuroinformatics 2011, Boston, MA, USA, September. [Proceedings]
  • Davison A.P. (2011) Automated tracking of scientific computations.
    AMP 2011: Reproducible Research-Tools and Strategies for Scientific Computing, Vancouver, Canada, July. [Slides] [Video] [Workshop website]
  • Raikov I., Cannon R., Clewley R., Cornelis H., Davison A.P., De Schutter E., Djurfeldt M., Gleeson P., Gorchetchnikov A., Plesser H.E., Hill S., Hines M., Kriener B., Le Franc Y., Lo C.-C., Morrison A., Muller E., Ray S., Schwabe L. and Szatmary B. (2011) NineML: the network interchange for neuroscience modeling language. BMC Neuroscience 12(Suppl 1): P330.
    CNS*2011, Stockholm, Sweden, July.
  • Davison A.P. (2011) Using PyNN and NineML.
    CNS*2011 workshop: Emerging standards for network modeling, Stockholm, Sweden, July.
  • Plesser H.E., Crook S., and Davison A.P. (2011) Reproducible models and reliable simulations: Current trends in computational neuroscience.
    SIAM Computational Science and Engineering 2011, Reno, Nevada, February.
  • Davison A.P., Brizzi T., Manette O., Monier C. and Frégnac Y. (2010) Helmholtz: a modular tool for neuroscience databases. Front. Neurosci. Conference Abstract doi:10.3389/conf.fnins.2010.13.00030
    Neuroinformatics 2010, Kobe, Japan, August. [Proceedings]
  • Davison A.P. (2010) Automated tracking of computational experiments using Sumatra.
    EuroSciPy 2010, Paris, France, July. [Slides] [Poster]
  • Gorchetchnikov A. and the INCF Multiscale Modeling Taskforce (2010) NineML - A description language for spiking neuron network modeling: the User Layer. BMC Neuroscience 11 (Suppl. 1): P71.
    CNS*2010, San Antonio, Texas, USA, July. [Proceedings]
  • Davison A.P. (2010) Challenges and solutions in replicability and provenance tracking for simulation projects. BMC Neuroscience 11 (Suppl. 1): P76.
    CNS*2010, San Antonio, Texas, USA, July. [Proceedings]
  • Raikov I. and the INCF Multiscale Modeling Taskforce (2010) NineML - A description language for spiking neuron network modeling: the Abstraction Layer. BMC Neuroscience 11 (Suppl. 1): P66.
    CNS*2010, San Antonio, Texas, USA, July. [Proceedings]
  • Davison A.P. (2010) Integration: a collaborative software tool-chain for neuromorphic computation.
    Frontiers in Neuromorphic Computation, Paris, France, June. [Slides]
  • Yger P., El Boustani S., Marre O., Davison A.P., Destexhe A. and Frégnac Y. (2009) Spatial organization of evoked neuronal dynamics in 2D recurrent networks, with or without structured stimulation. BMC Neuroscience 10 (Suppl1): P94.
    CNS*2009, Berlin, Germany, July. [Proceedings]
  • Davison A.P., Brüderle D., Kremkow J., Muller E., Pecevski D., Perrinet, L. and Yger, P. (2008) PyNN: a common interface for neuronal network simulators. Front. Neuroinform. Conference Abstract doi:10.3389/conf.neuro.11.2008.01.046
    Neuroinformatics 2008, Stockholm, Sweden, September. [Proceedings]
  • Yger P., Marre O., El Boustani S., Baudot P., Monier C., Levy M., Davison A.P. and Frégnac Y. (2007) Chaos control: Reliable signal propagation and pattern completion in chaotic neuronal networks.
    Society for Neuroscience Annual Meeting, San Diego, California, November.
  • Davison A.P., Yger P., Kremkow J., Perrinet L. and Muller E. (2007) PyNN: Towards a universal neural simulator API in Python. BMC Neuroscience 8 (Suppl. 2): P2.
    CNS*2007, Toronto, July. [Proceedings]
  • Davison A.P. (2006) Simulator-independent network modelling with Python and XML.
    Modeling the Brain's Labyrinth, Fodele, Crete, Greece, September.
  • Davison A.P., Yger P., Chan J.S., Newell F.N. and Frégnac Y. (2006) A combined psychophysical-modelling study of the mechanisms of tactile picture perception.
    CNS*2006, Edinburgh, U.K., July.
  • Davison A.P. (2006) NModLib: a database of components for neuroscience models.
    World Association of Modeling - Biologically Accurate Modeling Meeting, San Antonio, Texas, March.
  • Davison A.P., Belatreche A., Fieres J., Chan J.S., Newell F.N. and Frégnac Y. (2005) The Two-Ring paradigm: a computational approach to multisensory code binding.
    International SenseMaker Workshop on Life-Like Perception Systems, Derry, U.K., April.
  • Davison A.P. and Frégnac Y. (2004) Training a network of spiking neurons to perform coordinate transformations. Society for Neuroscience Abstracts 30: 177.4.
    Society for Neuroscience Annual Meeting, San Diego, California, November.
  • Davison A.P. (2004) Learning simple computations in spiking basis function networks using spike time-dependent plasticity. FENS Forum Abstracts 2: A224.4.
    FENS, Lisbon, Portugal, June.
  • Davison A.P., Hines M.L. and Shepherd G.M. (2002) Membrane bistability and sub-threshold oscillations in an olfactory bulb mitral cell model.
    AChemS XXIV, Sarasota, Florida, April.
  • Davison A.P., Zhou Z., Hines M.L. and Shepherd G.M. (2001) Simulating sodium and potassium currents in an olfactory mitral cell model.
    Society for Neuroscience Annual Meeting, San Diego, California, November.
  • Davison A.P., Feng J. and Brown D. (2001) Spike synchronization in a biophysically-detailed model of the olfactory bulb. Neurocomputing 38-40: 515-521.
    CNS*00, Brugge, Belgium, July. [Full text]
  • Davison A.P. and Feng J. (2001) A model of network interactions in the olfactory bulb.
    AChemS XXIII, Sarasota, Florida, April.
  • Davison A.P., Feng J. and Brown D. (1999) Structure of lateral inhibition in an olfactory bulb model. Lecture Notes in Computer Science 1606: 189-196.
    IWANN'99, Alicante, Spain, June.
  • Davison A.P., Miller T., Belton I., Bolton S. and Bonnett D.E. (1997) An assessment of image registration in the treatment planning of tumours of the brain.
    Radiology 1997 - Imaging, Science and Oncology, Birmingham, U.K., May.

Technical reports

  • Papadopoulo T., Viéville T. and Davison A.P. (2008) Towards generic tools for computational neuroscience: a perspective. FACETS Report D8-6. [PDF]
  • Davison A.P. and Papadopoulo T. (2008) Report on the second public release of the PyNN software and first public release of FacetsML validator and editor. FACETS Report D8-3. [PDF]
  • Davison A.P., Muller E. and Viéville T. (2006) Concept of a common data model for neuroscience simulations. FACETS Report D23. [PDF]
  • Davison A.P. and Viéville T. (2006) Definition of data formats for WP3 in the FACETS Knowledge Base. FACETS Report D11. [PDF]