/netpyne

A python package to facilitate the development of biological neuronal networks in NEURON

Primary LanguagePythonMIT LicenseMIT

NetPyNE (python package)

Description

A Python package to facilitate the development and simulation of biological networks in NEURON (NetPyNE Documentation)

NEURON/Python-based modularized framework for network simulations with MPI. Using this modularized structure, users can define different models (including cell types, populations, connectivities, etc.) just by modifying a single parameters file, and easily simulate then in NEURON. Additionally, the framework allows to store a single data file with the following:

  1. model specifications (conn rules etc)
  2. network instantiation (list of all cells, connections, etc)
  3. simulation parameters/configuration (duration, dt, etc)
  4. simulation output (spikes, voltage traces etc)

The data file is available in Pickle, JSON and Matlab formats.

Several example model parameters are provided, including:

  1. HHTut.py - simple tutorial model with a single Hodgkin-Huxley population and random connectivity
  2. HybridTut.py - simple tutorial model with a Hodgkin-Huxley and an Izhikevich populations, with random connectivity
  3. M1.py - mouse M1 model with 14 populations and cortical depth-dependent connectivity.

Additional details of the modelling framework can be found here:

Setup and execution

Requires NEURON with Python and MPI support.

  1. Install package via pip install netpyne.

  2. Create a model file (eg. model.py) where you import the netpyne package and set the parameters (you can use some of the parameter files included in the examples folder, e.g. HHTut.py):

    import HHTut
from netpyne import sim
sim.createSimulateAnalyze(
	simConfig = HHTut.simConfig,     
	netParams = HHTut.netParams)

  3. Type nrnivmodl mod. This should create a directory called either i686 or x86_64, depending on your computer's architecture.

  4. To run type python model.py (or mpiexec -np [num_proc] nrniv -python -mpi model.py for parallel simulation).

  5. The example mentioned above can be run with:

     cd examples/HHTut
 python HHTut_run.py

Overview of files:

  • examples/: Folder with examples.

  • doc/: Folder with documentation source files.

  • netpyne/: Folder with netpyne package files.

  • netpyne/sim.py: Contains all the model shared variables and modules. It is imported as "sim" from all other file, so that any variable or module can be referenced from any file using sim.varName

  • netpyne/simFunc.py: Simulation control functions (eg. runSim).

  • netpyne/network.py: Network related functions (eg. createCells)

  • netpyne/cell.py: contains cell and population classes to create cells based on the parameters.

  • netpyne/analysis.py: functions to visualize and analyse data

  • netpyne/default.py: default network and simulation parameters

  • netpyne/utils.py: utility python methods (eg. to import cell parameters)

Please cite as: "Salvador Dura-Bernal, Padraig Gleeson, Cliff C Kerr, Samuel Neymotin, William W Lytton. (2017). Neurosim-lab/NetPyNE: v0.6.7 [Data set]. Zenodo. http://doi.org/10.5281/zenodo.290623"

For further information please contact: salvadordura@gmail.com

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