Publications about, relating to or using PyNN

  • Kaplan BA, Lansner A, Masson GS and Perrinet LU (2013) Anisotropic connectivity implements motion-based prediction in a spiking neural network.
    Front. Comput. Neurosci. 7:112. doi: 10.3389/fncom.2013.00112
  • Galluppi, Francesco, Rast, Alexander, Davies, Sergio and Furber, Steve (2010) A general-purpose model translation system for a universal neural chip.
    Neural Information Processing. Theory and Algorithms; Lecture Notes in Computer Science vol 6443, pp58-65 [ link]
  • J. Nageswaran, N. Dutt, J. L. Krichmar, A. Nicolau, A. V. Veidenbaum (2009)
    A configurable simulation environment for the efficient simulation of large-scale spiking neural networks on graphics processors.
    Neural Networks 22:5-6, doi:10.1016/j.neunet.2009.06.028. [ link]
  • Davison AP, Hines M and Muller E (2009) Trends in programming languages for neuroscience simulations.
    Front. Neurosci. doi:10.3389/neuro.01.036.2009. [ link]
  • Davison AP, Brüderle D, Eppler J, Kremkow J, Muller E, Pecevski D, Perrinet L and Yger P (2009) PyNN: a common interface for neuronal network simulators.
    Front. Neuroinform. 2:11. doi:10.3389/neuro.11.011.2008. [ link]
  • Brüderle 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.
    Front. Neuroinform. 3:17. doi:10.3389/neuro.11.017.2009. [ link]
  • Bednar JA (2009) Topographica: building and analyzing map-level simulations from Python, C/C++, MATLAB, NEST, or NEURON components.
    Front. Neuroinform. 3:8. doi:10.3389/neuro.11.008.2009. [ link]
  • Goodman D and Brette R (2008) Brian: a simulator for spiking neural networks in Python.
    Front. Neuroinform. 2:5. doi:10.3389/neuro.11.005.2008. [ link]
  • Pecevski D, Natschläger T and Schuch K (2009) PCSIM: a parallel simulation environment for neural circuits fully integrated with Python.
    Front. Neuroinform. 3:11. doi:10.3389/neuro.11.011.2009. [ link]
  • Ray S and Bhalla US (2008) PyMOOSE: interoperable scripting in Python for MOOSE.
    Front. Neuroinform. 2:6. doi:10.3389/neuro.11.006.2008. [ link]
  • Sharon Crook, R Angus Silver and Padraig Gleeson (2009) Describing and exchanging models of neurons and neuronal networks with NeuroML.
    BMC Neuroscience, 10(Suppl 1):L1doi:10.1186/1471-2202-10-S1-L1. [ link]
  • D. Brüderle, A. Grübl, K. Meier, E. Muller and J. Schemmel (2007) A Software Framework for Tuning the Dynamics of Neuromorphic Silicon Towards Biology.
    LNCS 4507. doi:10.1007/978-3-540-73007-1. [ link]
  • B. Kaplan, D. Brüderle, J. Schemmel and K. Meier (2009) High-Conductance States on a Neuromorphic Hardware System.
    Proceedings of IJCNN 2009. [ link]
  • D. Brüderle (2009) Neuroscientific Modeling with a Mixed-Signal VLSI Hardware System.
    Doctoral Dissertation, Kirchhoff-Institute for Physics, University of Heidelberg. [ link]
  • A. Davison, P. Yger, J. Kremkow, L. Perrinet and E. Muller (2007) PyNN: towards a universal neural simulator API in Python.
    BMC Neuroscience 2007, 8(Suppl 2):P2. doi:10.1186/1471-2202-8-S2-P2. [ link]
  • E. Muller, A. P. Davison, T. Brizzi, D. Bruederle, M. J. Eppler, J. Kremkow, D. Pecevski, L. Perrinet, M. Schmuker and P. Yger (2009)
    NeuralEnsemble.Org: Unifying neural simulators in Python to ease the model complexity bottleneck.
    Frontiers in Autonomic Neuroscience. Conference Abstract: Neuroinformatics 2009. doi: 10.3389/conf.neuro.11.2009.08.104. [ link]