Institut NeuroPSI - UMR9197
CNRS Université Paris-Saclay
Gif-Sur-Yvette
France

Dr. Andrew Davison

Chargé de Recherche
Neuroinformatique

andrew.davison cnrs.fr
+33(0)1 69 82 34 51
ORCID : 0000-0002-4793-7541

Activités de recherche

I am a senior research scientist in the ICN department, where I lead the Neuroinformatics group. You might also be interested in my personal homepage or my Twitter feed.

See my ORCID account

See my personal homepage

My main research interests are in large-scale, data-constrained, biologically-detailed modelling of neuronal networks. My work at the moment has several strands:

  • development of tools to facilitate collaborative modelling, model sharing, and the use of novel hardware (GPU, neuromorphic) for neuronal simulations, notably PyNN, NineML and NeuroML.
  • promoting reproducible research in computational neuroscience and neuroinformatics, both through trying to spread best practices and through tool development (see the Sumatra project).
  • promoting neurophysiology data sharing, by participation in international standardisation efforts, by development of tools to harmonize the handling of electrophysiology data in Python (see the Neo project), and by development of a framework to simplify databasing of neurophysiology data in small labs (see the Helmholtz project).
  • development of models of the early visual system, from retina to primary visual cortex, in close collaboration with experimentalists.

Publications

Article dans une revue

2021

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Sára Sáray, Christian Rössert, Shailesh Appukuttan, Rosanna Migliore, Paola Vitale, et al.. HippoUnit: A software tool for the automated testing and systematic comparison of detailed models of hippocampal neurons based on electrophysiological data. PLoS Computational Biology, Public Library of Science, 2021, 17 (1), pp.e1008114. ⟨10.1371/journal.pcbi.1008114⟩. ⟨hal-03063383⟩
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https://hal.archives-ouvertes.fr/hal-03063383/file/2020.07.02.184333v2.full.pdf BibTex

2020

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Sharon Crook, Andrew P. Davison, Robert Mcdougal, Hans Ekkehard Plesser. Editorial: Reproducibility and Rigour in Computational Neuroscience. Frontiers in Neuroinformatics, Frontiers, 2020, 14, pp.23. ⟨10.3389/fninf.2020.00023⟩. ⟨hal-02913122⟩
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https://hal.archives-ouvertes.fr/hal-02913122/file/fninf-14-00023.pdf BibTex
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Kael Dai, Juan Hernando, Yazan Billeh, Sergey Gratiy, Judit Planas, et al.. The SONATA data format for efficient description of large-scale network models. PLoS Computational Biology, Public Library of Science, 2020, 16 (2), pp.e1007696. ⟨10.1371/journal.pcbi.1007696⟩. ⟨hal-02913116⟩
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https://hal.archives-ouvertes.fr/hal-02913116/file/journal.pcbi.1007696%20%281%29.pdf BibTex
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Andrew P. Davison. [Rp] Dendrodendritic inhibition and simulated odor responses in a detailed olfactory bulb network model. ReScience C, 2020, ⟨10.5281/zenodo.3972130⟩. ⟨hal-03046451⟩
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https://hal.archives-ouvertes.fr/hal-03046451/file/article-7.pdf BibTex

2019

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Padraig Gleeson, Matteo Cantarelli, Boris Marin, Adrian Quintana, Matt Earnshaw, et al.. Open Source Brain: A Collaborative Resource for Visualizing, Analyzing, Simulating, and Developing Standardized Models of Neurons and Circuits. Neuron, Elsevier, 2019, 103 (3), pp.395. ⟨10.1016/j.neuron.2019.05.019⟩. ⟨hal-02193259⟩
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https://hal.archives-ouvertes.fr/hal-02193259/file/PIIS0896627319304441.pdf BibTex

2018

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Ján Antolík, Andrew P. Davison. Arkheia: Data Management and Communication for Open Computational Neuroscience. Frontiers in Neuroinformatics, Frontiers, 2018, 12, pp.6. ⟨10.3389/fninf.2018.00006⟩. ⟨hal-01737956⟩
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https://hal.sorbonne-universite.fr/hal-01737956/file/fninf-12-00006.pdf BibTex
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Inga Blundell, Romain Brette, Thomas Cleland, Thomas Close, Daniel Coca, et al.. Code Generation in Computational Neuroscience: A Review of Tools and Techniques. Frontiers in Neuroinformatics, Frontiers, 2018, 12, pp.68. ⟨10.3389/fninf.2018.00068⟩. ⟨hal-01996352⟩
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https://hal.sorbonne-universite.fr/hal-01996352/file/fninf-12-00068.pdf BibTex

2017

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Stephen Eglen, Ben Marwick, Yaroslav Halchenko, Michael Hanke, Shoaib Sufi, et al.. Toward standard practices for sharing computer code and programs in neuroscience. Nature Neuroscience, Nature Publishing Group, 2017, 20 (6), pp.770-773. ⟨10.1038/nn.4550⟩. ⟨hal-02064847⟩
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Padraig Gleeson, Andrew P. Davison, R Angus Silver, Giorgio Ascoli. A Commitment to Open Source in Neuroscience. Neuron, Elsevier, 2017, 96 (5), pp.964-965. ⟨10.1016/j.neuron.2017.10.013⟩. ⟨hal-02064834⟩
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Nicolas Rougier, Konrad Hinsen, Frédéric Alexandre, Thomas Arildsen, Lorena Barba, et al.. Sustainable computational science: the ReScience initiative. PeerJ Computer Science, PeerJ, 2017, 3, pp.e142. ⟨10.7717/peerj-cs.142⟩. ⟨hal-01592078⟩
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https://arxiv.org/pdf/1707.04393 BibTex
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Leonid L. Rubchinsky, Sungwoo Ahn, Wouter Klijn, Ben Cumming, Stuart Yates, et al.. 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 2. BMC Neuroscience, BioMed Central, 2017, 18 (Suppl 1), pp.59. ⟨10.1186/s12868-017-0371-2⟩. ⟨hal-01580190⟩
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https://hal.inria.fr/hal-01580190/file/12868_2017_Article_371.pdf BibTex

2016

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Christophe Pouzat, Andrew P. Davison, Konrad Hinsen. La recherche reproductible : une communication scientifique explicite. Statistique et Société, Société française de statistique, 2016, Deux débats sur les données, 3 (1). ⟨hal-01478360⟩
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2015

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Eilif Muller, James A Bednar, Markus Diesmann, Marc-Oliver Gewaltig, Michael Hines, et al.. Python in neuroscience.. Frontiers in Neuroinformatics, Frontiers, 2015, 9, pp.11. ⟨10.3389/fninf.2015.00011⟩. ⟨hal-01159440⟩
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2014

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Mikael Djurfeldt, Andrew P. Davison, Jochen M Eppler. Efficient generation of connectivity in neuronal networks from simulator-independent descriptions.. Front Neuroinform, 2014, 8, pp.43. ⟨10.3389/fninf.2014.00043⟩. ⟨hal-01055563⟩
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Samuel Garcia, Domenico Guarino, Florent Jaillet, Todd Jennings, Robert Pröpper, et al.. Neo: an object model for handling electrophysiology data in multiple formats.. Front Neuroinform, 2014, 8, pp.10. ⟨10.3389/fninf.2014.00010⟩. ⟨hal-01055571⟩
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Michael Vella, Robert C Cannon, Sharon M. Crook, Andrew P. Davison, Gautham Ganapathy, et al.. libNeuroML and PyLEMS: using Python to combine procedural and declarative modeling approaches in computational neuroscience.. Front Neuroinform, 2014, 8, pp.38. ⟨10.3389/fninf.2014.00038⟩. ⟨hal-01055565⟩
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2013

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Ján Antolík, Andrew P. Davison. Integrated workflows for spiking neuronal network simulations.. Front Neuroinform, 2013, 7, pp.34. ⟨10.3389/fninf.2013.00034⟩. ⟨hal-01055572⟩
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2012

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Sharon M. Crook, James A Bednar, Sandra Berger, Robert Cannon, Andrew P. Davison, et al.. Creating, documenting and sharing network models.. Network: Computation in Neural Systems, Taylor & Francis, 2012, 23 (4), pp.131-49. ⟨10.3109/0954898X.2012.722743⟩. ⟨hal-01055577⟩
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Andrew P. Davison. Automated Capture of Experiment Context for Easier Reproducibility in Computational Research. Computing in Science and Engineering, Institute of Electrical and Electronics Engineers, 2012, 14 (4), pp.48-56. ⟨10.1109/MCSE.2012.41⟩. ⟨hal-01055702⟩
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Andrew P. Davison. Collaborative modelling: the future of computational neuroscience?. Network: Computation in Neural Systems, Taylor & Francis, 2012, 23 (4), pp.157-66. ⟨10.3109/0954898X.2012.718482⟩. ⟨hal-01055579⟩
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2011

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Daniel Brüderle, Mihai A Petrovici, Bernhard Vogginger, Matthias Ehrlich, Thomas Pfeil, et al.. A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems.. Biological Cybernetics (Modeling), Springer Verlag, 2011, 104 (4-5), pp.263-96. ⟨10.1007/s00422-011-0435-9⟩. ⟨hal-00635967⟩
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2010

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Padraig Gleeson, Sharon M. Crook, Robert C Cannon, Michael L Hines, Guy O Billings, et al.. NeuroML: a language for describing data driven models of neurons and networks with a high degree of biological detail.. PLoS Computational Biology, Public Library of Science, 2010, 6 (6), pp.e1000815. ⟨10.1371/journal.pcbi.1000815⟩. ⟨hal-00586776⟩
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2009

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Daniel Brüderle, Eric Muller, Andrew Davison, Eilif Muller, Johannes Schemmel, et al.. Establishing a Novel Modeling Tool: A Python-based Interface for a Neuromorphic Hardware System. Frontiers in Neuroinformatics, Frontiers, 2009, 3, pp.17. ⟨10.3389/neuro.11.017.2009⟩. ⟨hal-03047041⟩
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Andrew P. Davison, Daniel Brüderle, Jochen Eppler, Jens Kremkow, Eilif Muller, et al.. PyNN: A Common Interface for Neuronal Network Simulators.. Frontiers in Neuroinformatics, Frontiers, 2009, 2, pp.11. ⟨10.3389/neuro.11.011.2008⟩. ⟨hal-00586786⟩
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https://hal.archives-ouvertes.fr/hal-00586786/file/davison-08.pdf BibTex
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Andrew P. Davison, Michael L Hines, Eilif Muller. Trends in programming languages for neuroscience simulations.. Frontiers in Neuroscience, Frontiers, 2009, 3 (3), pp.374-80. ⟨10.3389/neuro.01.036.2009⟩. ⟨hal-00586787⟩
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Michael L Hines, Andrew P. Davison, Eilif Muller. NEURON and Python.. Front Neuroinformatics, 2009, 3, pp.1. ⟨10.3389/neuro.11.001.2009⟩. ⟨hal-00586782⟩
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Olivier Marre, Pierre Yger, Andrew P. Davison, Yves Frégnac. Reliable recall of spontaneous activity patterns in cortical networks.. Journal of Neuroscience, Society for Neuroscience, 2009, 29 (46), pp.14596-606. ⟨10.1523/JNEUROSCI.0753-09.2009⟩. ⟨hal-00444943⟩
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2007

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Romain Brette, Michael Rudolph, Ted Carnevale, Michael Hines, David Beeman, et al.. Simulation of networks of spiking neurons: A review of tools and strategies.. Journal of Computational Neuroscience, Springer Verlag, 2007, 23 (3), pp.349-98. ⟨10.1007/s10827-007-0038-6⟩. ⟨hal-00180662⟩
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2006

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Mathilde Badoual, Quan Zou, Andrew P. Davison, Michael Rudolph, Thierry Bal, et al.. Biophysical and phenomenological models of multiple spike interactions in spike-timing dependent plasticity.. Int J Neural Syst, 2006, 16 (2), pp.79-97. ⟨hal-00120626⟩
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Andrew P. Davison, Yves Frégnac. Learning cross-modal spatial transformations through spike timing-dependent plasticity.. Journal of Neuroscience, Society for Neuroscience, 2006, 26 (21), pp.5604-15. ⟨10.1523/JNEUROSCI.5263-05.2006⟩. ⟨hal-00120625⟩
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2004

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Andrew P. Davison, Thomas M Morse, Michele Migliore, Gordon M Shepherd, Michael L Hines. Semi-automated population of an online database of neuronal models (ModelDB) with citation information, using PubMed for validation.. Neuroinformatics, Springer, 2004, 2 (3), pp.327-32. ⟨10.1385/NI:2:3:327⟩. ⟨hal-00299855⟩
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2003

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Andrew P. Davison, Jianfeng Feng, David Brown. Dendrodendritic inhibition and simulated odor responses in a detailed olfactory bulb network model.. Journal of Neurophysiology, American Physiological Society, 2003, 90 (3), pp.1921-35. ⟨10.1152/jn.00623.2002⟩. ⟨hal-00299879⟩
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Michele Migliore, Thomas M Morse, Andrew P. Davison, Luis Marenco, Gordon M Shepherd, et al.. ModelDB: making models publicly accessible to support computational neuroscience.. Neuroinformatics, Springer, 2003, 1 (1), pp.135-9. ⟨10.1385/NI:1:1:135⟩. ⟨hal-00586793⟩
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2000

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Andrew P. Davison, J. Feng, D. Brown. A reduced compartmental model of the mitral cell for use in network models of the olfactory bulb.. Brain Research Bulletin, Elsevier, 2000, 51 (5), pp.393-9. ⟨hal-00635986⟩
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Communication dans un congrès

2013

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Andrew P. Davison, Thierry Bal, Domenico Guarino, Olivier Manette, Cyril Monier, et al.. Helmholtz: a customizable framework for neurophysiology data management. Neuroinformatics 2013, INCF, Stockholm, Sweden, Aug 2013, Stockholm, Sweden. ⟨10.3389/conf.fninf.2013.09.00025⟩. ⟨hal-03047325⟩
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2008

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Olivier Marre, Pierre Yger, Andrew Davison, Yves Frégnac. Reliable recall of spontaneous activity patterns in chaotic cortical networks. Deuxième conférence française de Neurosciences Computationnelles, "Neurocomp08", Oct 2008, Marseille, France. ⟨hal-00331545⟩
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https://hal.archives-ouvertes.fr/hal-00331545/file/NEUROCOMP2008_0028.pdf BibTex
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Pierre Yger, Abigail Morrison, M. Diesmann, Andrew P. Davison, Yves Frégnac. STDP in topogra-phical neuronal networks.. Proceedings of the 44th Japan Workshop - ISTC-RIKEN BSI, 2008, Wako, Japan. pp.en cours. ⟨hal-00382367⟩
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2007

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Mathilde Badoual, Thierry Bal, Pierre Baudot, Andrew P. Davison, Alain Destexhe, et al.. Plasticité associative dépendante de l'ordre temporel entre activités pré- et post-synaptiques (Spike Timing Dependent Plasticity) : son implication dans l'adaptation fonctionnelle des réseaux sensoriels et l'apprentissage perceptif.. Colloque de l'ACI (Action Concertée Incitative) Neurosciences Intégratives et Computationnelles, 2007, Paris, France. pp.en cours. ⟨hal-00380905⟩
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Andrew P. Davison, Pierre Yger, Jens Kremkow, Laurent Perrinet, Eilif Muller. PyNN: Towards a universal neural simulator API in Python.. CNS 2007 Proceedings of the 16th Annual Computational Neuroscience Meeting, 2007, Toronto, Canada. pp.73. ⟨hal-00381688⟩
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2006

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Andrew P. Davison, Pierre Yger, Yves Frégnac, J. Chan, F. Newell. A combined pyschophysical--modelling investigation of the mechanisms of tactile picture perception.. Proceedings of the 15th Annual Computational Neuroscience Meeting, 2006, Edinburgh, United Kingdom. pp.170. ⟨hal-00380061⟩
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2004

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Andrew P. Davison, Yves Frégnac. Training a network of spiking neurons to perform coordinate transformations.. 34th Annual Meeting of the Society for Neuroscience, 2004, San Diego, United States. pp.4. ⟨hal-00379386⟩
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Andrew P. Davison. Learning simple computations in spiking basis function networks using spike time-dependent plasticity.. 4th Forum of European Neuroscience, 2004, Lisbon, Portugal. pp.A224. ⟨hal-00379381⟩
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2000

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Andrew P. Davison, Jf Feng, D. Brown. Spike synchronization in a biophysically-detailed model of the olfactory bulb. 9th Annual Computational Neuroscience Meeting, 2000, Brugge, Belgium. pp.515-521, ⟨10.1016/S0925-2312(01)00391-5⟩. ⟨hal-01055784⟩
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Chapitre d'ouvrage

2007

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Yves Frégnac, Michael Rudolph, Andrew P. Davison, Alain Destexhe. Complexity and level hierarchy in neural networks. François Képès. Biological networks, World Scientific Publishing Company, pp.1-52, 2007, Complex Systems and Interdisciplinary Science, vol. 3. ⟨hal-00211742⟩
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Yves Frégnac, Michael Rudolph, Andrew P. Davison, Alain Destexhe. Complexity in Neuronal Networks. François Képès. Biological Networks, World Scientific, pp.291-338, 2007, Complex Systems and Interdisciplinary Science vol.3, 9789812706959. ⟨hal-00739550⟩
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2004

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Andrew P. Davison. Biologically-Detailed Network Modelling. Jianfeng Feng. Computational Neuroscience. A Comprehensive Approach, Chapman & Hall / CRC Press, pp.287-304, 2004, Chapman & Hall/CRC Mathematical Biology and Medicine. ⟨hal-00377318⟩
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Logiciel

2021

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Shailesh Appukuttan, Andrew P. Davison. HBP Model Validation Framework v1.7. 2021. ⟨hal-03330341⟩
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https://hal.archives-ouvertes.fr/hal-03330341/file/hbp-validation-framework-1.7.zip BibTex
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Andrew P. Davison, Onur Ates, Corentin Fragnaud. Neo Viewer v1.4.0. 2021. ⟨hal-03330213⟩
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https://hal.archives-ouvertes.fr/hal-03330213/file/neo-viewer-1.4.0.zip BibTex
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Andrew P. Davison, Jonathan Duperrier. HBP Neuromorphic Computing Platform version 2021A. 2021. ⟨hal-03330386⟩
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https://hal.archives-ouvertes.fr/hal-03330386/file/hbp_neuromorphic_platform-2021A.zip BibTex

2020

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Andrew P. Davison, Laurent U Perrinet, Onur Ates, Eric Müller, Rémy Cagnol, et al.. PyNN v0.9.6. 2020. ⟨hal-03330164⟩
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https://hal.archives-ouvertes.fr/hal-03330164/file/PyNN-0.9.6.zip BibTex
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Julia Sprenger, Samuel Garcia, Alexander Kleinjohann, Hugo van Kemenade, Achileas Koutsou, et al.. Neo v0.9.0. 2020. ⟨hal-03330047⟩
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https://hal.archives-ouvertes.fr/hal-03330047/file/python-neo-0.9.0.zip BibTex

2019

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Andrew P. Davison, Glynis Mattheisen, Yann Zerlaut. fairgraph v0.5.1. 2019. ⟨hal-03330091⟩
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https://hal.archives-ouvertes.fr/hal-03330091/file/fairgraph-0.5.1.zip BibTex
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Achileas Koutsou, Chek Choi, Richard Gerkin, Hugo van Kemenade, Alexander Kleinjohann, et al.. Neo v0.8.0. 2019. ⟨hal-03329305⟩
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https://hal.archives-ouvertes.fr/hal-03329305/file/python-neo-0.8.0.zip BibTex