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Biophysics-based prediction of LFPs from point-neuron networks

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Module hybridLFPy

Python module implementating a hybrid model scheme for predictions of extracellular potentials (local field potentials, LFPs) of spiking neuron network simulations.

Development

The module hybridLFPy was mainly developed in the Computational Neuroscience Group (http://compneuro.umb.no), Department of Mathemathical Sciences and Technology (http://www.nmbu.no/imt), at the Norwegian University of Life Sciences (http://www.nmbu.no), Aas, Norway, in collaboration with Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6), Juelich Research Centre and JARA, Juelich, Germany (http://www.fz-juelich.de/inm/inm-6/EN/).

Citation

Espen Hagen, David Dahmen, Maria L. Stavrinou, Henrik Lindén, Tom Tetzlaff, Sacha J. van Albada, Sonja Grün, Markus Diesmann, Gaute T. Einevoll; Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks, Cerebral Cortex, Volume 26, Issue 12, 1 December 2016, Pages 4461–4496, https://doi.org/10.1093/cercor/bhw237

Bibtex source: ::

@article{doi:10.1093/cercor/bhw237,
author = {Hagen, Espen and Dahmen, David and Stavrinou, Maria L. and Lindén, Henrik and Tetzlaff, Tom and van Albada, Sacha J. and Grün, Sonja and Diesmann, Markus and Einevoll, Gaute T.},
title = {Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks},
journal = {Cerebral Cortex},
volume = {26},
number = {12},
pages = {4461-4496},
year = {2016},
doi = {10.1093/cercor/bhw237},
URL = { + http://dx.doi.org/10.1093/cercor/bhw237},
eprint = {/oup/backfile/content_public/journal/cercor/26/12/10.1093_cercor_bhw237/2/bhw237.pdf}
}   

Tutorial slides

Slides from OCNS 2015 meeting tutorial T2: Modeling and analysis of extracellular potentials <http://www.cnsorg.org/cns-2015-tutorials#t2>_ hosted in Prague, Czech Republic on LFPy and hybridLFPy: CNS2015_LFPy_tutorial.pdf <http://LFPy.github.io/downloads/CNS2015_LFPy_tutorial.pdf>_

License

This software is released under the General Public License (see LICENSE file).

Warranty

This software comes without any form of warranty.

Installation

First download all the hybridLFPy source files using git (http://git-scm.com). Open a terminal window and type: ::

cd $HOME/where/to/put/hybridLFPy
git clone https://github.com/INM-6/hybridLFPy.git

To use hybridLFPy from any working folder without copying files, run: ::

(sudo) python setup.py develop (--user)

Installing it is also possible, but not recommended as things might change with pulls from the repository: ::

(sudo) python setup.py install (--user)

examples folder

Some example script(s) on how to use this module

docs folder

Source files for autogenerated documentation using Sphinx.

To compile documentation source files in this directory using sphinx, use: ::

sphinx-build -b html docs documentation

Online documentation

The sphinx-generated html documentation can be accessed at http://INM-6.github.io/hybridLFPy

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Biophysics-based prediction of LFPs from point-neuron networks

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