NEURON + Python (Hines et al. 2009)

 Download zip file   Auto-launch 
Help downloading and running models
Accession:116491
The NEURON simulation program now allows Python to be used alone or in combination with NEURON's traditional Hoc interpreter. Adding Python to NEURON has the immediate benefit of making available a very extensive suite of analysis tools written for engineering and science. It also catalyzes NEURON software development by offering users a modern programming tool that is recognized for its flexibility and power to create and maintain complex programs. At the same time, nothing is lost because all existing models written in Hoc, including GUI tools, continue to work without change and are also available within the Python context. An example of the benefits of Python availability is the use of the xml module in implementing NEURON's Import3D and CellBuild tools to read MorphML and NeuroML model specifications.
Reference:
1 . Hines ML, Davison AP, Muller E (2009) NEURON and Python Frontiers in Neuroinformatics 3:1 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type:
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; NeuroML; Python;
Model Concept(s): Methods;
Implementer(s): Hines, Michael [Michael.Hines at Yale.edu]; Davison, Andrew [Andrew.Davison at iaf.cnrs-gif.fr];
/
nrnpython
README
ch6_model.py
mosinit.hoc
ref_example.py
                            
This is the readme for

Hines ML, Davison AP, Muller E. (2009) NEURON and Python
Frontiers in Neuroinformatics 3:1

Code listings of Figures 1-3. Launch using
nrniv -python ch6_model.py
Requires
NEURON -- VERSION 7.0 (228:fbb244f333a9) 2008-11-25
or later.


Hines ML, Davison AP, Muller E (2009) NEURON and Python Frontiers in Neuroinformatics 3:1[PubMed]

References and models cited by this paper

References and models that cite this paper

Abrahams D, Grosse-kunstleve RW (2003) Building hybrid systems with Boost.Python C-++ Users J

Beazley DM (1996) SWIG: an easy to use tool for integrating scripting languages with C and C++ Proceedings of the 4th Annual USENIX Tcl-Tk Workshop, Monterey, CA.

Carnevale NT, Hines ML (2006) The NEURON Book

Crook S, Gleeson P, Howell F, Svitak J, Silver RA (2007) MorphML: level 1 of the NeuroML standards for neuronal morphology data and model specification. Neuroinformatics 5:96-104 [PubMed]

Dalcín L, Paza R, Stortia M, DEliaa J (2008) MPI for Python:performance improvements and MPI-2 extensions J Parallel Distrib Comput 68:655-662

Dubois PF (2007) Python: batteries included Ieee Comput Sci Eng 9:7-9

Gabriel E, Fagg GE, Bosilca G, Angskun T, Dongarra JJ, Squyres JM, Sahay V, Kambadur P, Barre (2004) Open MPI: goals, concept, and design of a next generation MPI implementation Proceedings, 11th European PVM-MPI Users' Group Meeting, Kranzlmuller D:Kacsuk P:Dongara J, ed. pp.97

Goddard NH, Hucka M, Howell F, Cornelis H, Shankar K, Beeman D (2001) Towards NeuroML: model description methods for collaborative modelling in neuroscience. Philos Trans R Soc Lond B Biol Sci 356:1209-28 [PubMed]

Gropp W (2002) MPICH2: a new start for MPI implementations Proceedings of the 9th European PVM-MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface, Kranzlmuller D:Kacsuk P:Dongara J:Volkert J, ed. pp.7

Hines ML, Carnevale NT (2000) Expanding NEURON's repertoire of mechanisms with NMODL. Neural Comput 12:995-1007 [PubMed]

Hines ML, Carnevale NT (2008) Translating network models to parallel hardware in NEURON J. Neurosci. Meth. 169:425-455 [Journal] [PubMed]

   Translating network models to parallel hardware in NEURON (Hines and Carnevale 2008) [Model]

Hines ML, Markram H, Schuermann F (2008) Fully Implicit Parallel Simulation of Single Neurons J Comp Neurosci 25:439-448 [Journal] [PubMed]

   Fully Implicit Parallel Simulation of Single Neurons (Hines et al. 2008) [Model]

Hunter JD (2007) Matplotlib: a 2D graphics environment Ieee Comput Sci Eng 9:90-95

Jones E, Oliphant T, Peterson P, Et_al (2001) http:--www.scipy.org- SciPy: open source scientific tools for Python

Kernighan BW, Pike R (1984) The UNIX Programming Environment Hoc Manual :329-333

Migliore M, Cannia C, Lytton WW, Markram H, Hines ML (2006) Parallel Network Simulations with NEURON. J Comp Neurosci 21:110-119 [Journal] [PubMed]

   Parallel network simulations with NEURON (Migliore et al 2006) [Model]

Oliphant TE (2007) Python for scientific computing Ieee Comput Sci Eng 9:10-20

Prez F, Granger BE (2007) IPython: a system for interactive scientific computing Ieee Comput Sci Eng 9:21-29

Allken V, Chepkoech J-L, Einevoll GT, Halnes G (2014) The subcellular distribution of T-type Ca++ channels in interneurons of the lateral geniculate nucleus PLoS ONE 9(9):e107780 [Journal] [PubMed]

   The subcellular distribution of T-type Ca2+ channels in LGN interneurons (Allken et al. 2014) [Model]

Bahl A, Stemmler MB, Herz AV, Roth A (2012) Automated optimization of a reduced layer 5 pyramidal cell model based on experimental data. J Neurosci Methods 210:22-34 [Journal] [PubMed]

   A set of reduced models of layer 5 pyramidal neurons (Bahl et al. 2012) [Model]

Brette R, Goodman DF (2011) Vectorized Algorithms for Spiking Neural Network Simulation. Neural Comput [Journal] [PubMed]

   Vectorized algorithms for spiking neural network simulation (Brette and Goodman 2011) [Model]

Cazé RD, Jarvis S, Foust AJ, Schultz SR (2017) Dendrites Enable a Robust Mechanism for Neuronal Stimulus Selectivity. Neural Comput :1-17 [Journal] [PubMed]

   Dendrites enable a robust mechanism for neuronal stimulus selectivity (Caze et al 2017) [Model]

Chen W, De Schutter E (2014) Python-based geometry preparation and simulation visualization toolkits for STEPS Front. Neuroinform. 8:37 [Journal]

   Python-based toolkits for STEPS (Chen and De Schutter 2014) [Model]

Eguchi A, Neymotin SA and Stringer SM (2014) Color opponent receptive fields self-organize in a biophysical model of visual cortex via spike-timing dependent plasticity 8:16. doi: Front. Neural Circuits 8:16 [Journal]

   Simulated cortical color opponent receptive fields self-organize via STDP (Eguchi et al., 2014) [Model]

Friedrich P, Vella M, Gulyas AI, Freund TF, Kali S (2014) A flexible, interactive software tool for fitting the parameters of neuronal models. Front Neuroinform 8:63 [Journal] [PubMed]

   Software (called Optimizer) for fitting neuronal models (Friedrich et al. 2014) [Model]

Gleeson P, Crook S, Cannon RC, Hines ML, Billings GO, Farinella M, Morse TM, Davison AP, Ray (2010) NeuroML: a language for describing data driven models of neurons and networks with a high degree of biological detail. PLoS Comput Biol 6:e1000815 [Journal] [PubMed]

Grienberger C, Milstein AD, Bittner KC, Romani S, Magee JC (2017) Inhibitory suppression of heterogeneously tuned excitation enhances spatial coding in CA1 place cells. Nat Neurosci [Journal] [PubMed]

   CA1 pyr cell: Inhibitory modulation of spatial selectivity+phase precession (Grienberger et al 2017) [Model]

Halnes G, Mäki-Marttunen T, Keller D, Pettersen KH, Andreassen OA, Einevoll GT (2016) Effect of Ionic Diffusion on Extracellular Potentials in Neural Tissue PLoS Comput Biol 12:e1005193 [Journal] [PubMed]

   Effect of ionic diffusion on extracellular potentials (Halnes et al 2016) [Model]

Hernandez OE, Zurek EE (2013) Teaching and learning the Hodgkin-Huxley model based on software developed in NEURON's programming language hoc. BMC Med Educ 13:70 [Journal] [PubMed]

   Software for teaching the Hodgkin-Huxley model (Hernandez & Zurek 2013) (SENB written in NEURON hoc) [Model]

Huang S, Hong S, De Schutter E (2015) Non-linear leak currents affect mammalian neuron physiology. Front Cell Neurosci 9:432 [Journal] [PubMed]

   Concentration dependent nonlinear K+ and Cl- leak current (Huang et al. 2015) [Model]

Lytton WW, Seidenstein AH, Dura-Bernal S, McDougal RA, Schurmann F, Hines ML (2016) Simulation Neurotechnologies for Advancing Brain Research: Parallelizing Large Networks in NEURON. Neural Comput :1-28 [Journal] [PubMed]

   Parallelizing large networks in NEURON (Lytton et al. 2016) [Model]

Masoli S, Solinas S, D'Angelo E (2015) Action potential processing in a detailed Purkinje cell model reveals a critical role for axonal compartmentalization. Front Cell Neurosci 9:47 [Journal] [PubMed]

   A detailed Purkinje cell model (Masoli et al 2015) [Model]

Mattioni M, Cohen U, Le Novere N (2012) Neuronvisio: A Graphical User Interface with 3D Capabilities for NEURON. Front Neuroinform 6:20 [Journal] [PubMed]

   Neuronvisio: a gui with 3D capabilities for NEURON (Mattioni et al. 2012) [Model]

Mattioni M, Le Novere N (2013) Integration of Biochemical and Electrical Signaling-Multiscale Model of the Medium Spiny Neuron of the Striatum. PLoS One 8:e66811 [Journal] [PubMed]

   Multiscale simulation of the striatal medium spiny neuron (Mattioni & Le Novere 2013) [Model]

McColgan T, Liu J, Kuokkanen PT, Carr CE, Wagner H, Kempter R (2017) Dipolar extracellular potentials generated by axonal projections. Elife [Journal] [PubMed]

   Dipolar extracellular potentials generated by axonal projections (McColgan et al 2017) [Model]

McDougal RA, Bulanova AS, Lytton WW (2016) Reproducibility in computational neuroscience models and simulations IEEE Trans Biomed Eng 63(10):2021-2035 [Journal] [PubMed]

McDougal RA, Hines ML, Lytton WW (2013) Reaction-diffusion in the NEURON simulator. Front Neuroinform 7:28 [Journal] [PubMed]

   Reaction-diffusion in the NEURON simulator (McDougal et al 2013) [Model]

Miceli S, Ness TV, Einevoll GT, Schubert D (2017) Impedance Spectrum in Cortical Tissue: Implications for Propagation of LFP Signals on the Microscopic Level Eneuro 4:1-15 [Journal]

   Impedance spectrum in cortical tissue: implications for LFP signal propagation (Miceli et al. 2017) [Model]

Neymotin SA, Hilscher MM, Moulin TC, Skolnick Y, Lazarewicz MT, Lytton WW (2013) Ih Tunes Theta/Gamma Oscillations and Cross-Frequency Coupling In an In Silico CA3 Model PLoS ONE 8(10):e76285 [Journal] [PubMed]

   Ih tunes oscillations in an In Silico CA3 model (Neymotin et al. 2013) [Model]

Neymotin SA, Lazarewicz MT, Sherif M, Contreras D, Finkel LH, Lytton WW (2011) Ketamine disrupts theta modulation of gamma in a computer model of hippocampus Journal of Neuroscience 31(32):11733-11743 [Journal] [PubMed]

   Ketamine disrupts theta modulation of gamma in a computer model of hippocampus (Neymotin et al 2011) [Model]

Olivares E, Salgado S, Maidana JP, Herrera G, Campos M, Madrid R, Orio P (2015) TRPM8-dependent dynamic response in a mathematical model of cold thermoreceptor PLOS One 10(10):e0139314 [Journal] [PubMed]

   TRPM8-dependent dynamic response in cold thermoreceptors (Olivares et al. 2015) [Model]

Ona-Jodar T, Gerkau NJ, Aghvami SS, Rose CR, Egger V (2017) Two-Photon Na+ Imaging Reports Somatically Evoked Action Potentials in Rat Olfactory Bulb Mitral and Granule Cell Neurites Front. Cell. Neurosci. 11:50 [Journal]

   Na+ Signals in olfactory bulb neurons (granule cell model) (Ona-Jodar et al. 2017) [Model]

Sanjay M, Neymotin SA, Krothapalli SB (2015) Impaired dendritic inhibition leads to epileptic activity in a computer model of CA3. Hippocampus 25:1336-50 [Journal] [PubMed]

   CA3 Network Model of Epileptic Activity (Sanjay et. al, 2015) [Model]

Tikidji-Hamburyan RA, Narayana V, Bozkus Z, El-Ghazawi TA (2017) Software for Brain Network Simulations: A Comparative Study Front. Neuroinform. [Journal]

   Brain networks simulators - a comparative study (Tikidji-Hamburyan et al 2017) [Model]

Tomsett RJ, Ainsworth M, Thiele A, Sanayei M, Chen X, Gieselmann MA, Whittington MA, Cunningh (2015) Virtual Electrode Recording Tool for EXtracellular potentials (VERTEX): comparing multi-electrode recordings from simulated and biological mammalian cortical tissue. Brain Struct Funct 220(4):2333-53 [Journal] [PubMed]

   Large-scale model of neocortical slice in vitro exhibiting persistent gamma (Tomsett et al. 2014) [Model]

Torben-Nielsen B, Segev I, Yarom Y (2012) The generation of phase differences and frequency changes in a network model of inferior olive subthreshold oscillations. PLoS Comput Biol 8:e1002580 [Journal] [PubMed]

   Inferior Olive, subthreshold oscillations (Torben-Nielsen, Segev, Yarom 2012) [Model]

Williams AH, O'Donnell C, Sejnowski TJ, O'Leary T (2016) Dendritic trafficking faces physiologically critical speed-precision tradeoffs. Elife [Journal] [PubMed]

Zylbertal A, Kahan A, Ben-Shaul Y, Yarom Y, Wagner S (2015) Prolonged Intracellular Na+ Dynamics Govern Electrical Activity in Accessory Olfactory Bulb Mitral Cells PLOS Biology 13(12):e1002319 [Journal]

   AOB mitral cell: persistent activity without feedback (Zylbertal et al., 2015) [Model]

Zylbertal A, Yarom Y, Wagner S (2017) Synchronous infra-slow bursting in the mouse accessory olfactory bulb emerge from interplay between intrinsic neuronal dynamics and network connectivity. J Neurosci [Journal] [PubMed]

   A network of AOB mitral cells that produces infra-slow bursting (Zylbertal et al. 2017) [Model]

(49 refs)